From dce0d3de26d5b247bba1ae56db8e3cfc66319beb Mon Sep 17 00:00:00 2001 From: sundy1994 Date: Thu, 19 Dec 2024 15:43:12 -0800 Subject: [PATCH 1/3] add LIWC tests and loading checks --- .gitignore | 6 +- .../features/assets/lexicons_dict.pkl | Bin 123480 -> 123641 bytes src/team_comm_tools/utils/check_embeddings.py | 153 +- tests/data/cleaned_data/test_chat_level.csv | 2056 +++++++++++------ .../generate_liwc_tests_new.ipynb | 360 +++ 5 files changed, 1774 insertions(+), 801 deletions(-) create mode 100644 tests/ipython_notebooks/generate_liwc_tests_new.ipynb diff --git a/.gitignore b/.gitignore index 52f9f9af..524f3aed 100644 --- a/.gitignore +++ b/.gitignore @@ -35,6 +35,7 @@ MANIFEST src/team_comm_tools/features/lexicons/liwc_lexicons/* src/team_comm_tools/features/lexicons/liwc_lexicons_small_test/* src/team_comm_tools/features/lexicons/certainty.txt +src/team_comm_tools/features/lexicons/liwc_2015.dic src/team_comm_tools/modules/ src/team_comm_tools/output/* src/team_comm_tools/ipython_notebooks/.ipynb_checkpoints/ @@ -57,7 +58,4 @@ node_modules/ # testing /output /vector_data -test.py - - - +test.py \ No newline at end of file diff --git a/src/team_comm_tools/features/assets/lexicons_dict.pkl b/src/team_comm_tools/features/assets/lexicons_dict.pkl index 324de5e3e119fc93f9479c9fd9bfd829c070b10b..cc62bf43b0e9cbabc655f2fe8f26f2ada739b9c3 100644 GIT binary patch literal 123641 zcmcejUL804-Sx}2|NS5Q-tYZ-{c<|*p6-X^ z?t1<8`k()LeY)SSx7BgGKR(<0W%sIre_-F^_lI|T+rOSq*Xw?r zU-!q=cK6%+D&G(L)p~!}-}3$Xa=IV3-yCoDYkxa_GvB`Xw6kyb<92u5Uv~M+jeeL_ z?ImlT?$0l`Y|>t`ntzD~&zIBsuzSt+qVL&tRD7E~*-Q4cW<-q2#^>YlpWAc%diVLf z+thpmTK0?AJ%Ik0{lDI?HE2EOn5{h8I_`G0E_%*M>N)HCgnb?Jn6Ht9seh zsC@1|4=wO+oAvI;w-t*MYpv(Ri?{vtrJfB!-lqX5`m`0xA2ao=571VJEVs$}Z}m8) z$}ohHHao9yJY8P-rQ<29yt2p3>h{9aRO&OaM-4Vw&{*fA&-8t_x*T&9wq*7@Es=Mu zC$D-~ZEB%394|HSW?x4ii+c6128e3W9yC9DFc53JVD%|m2>3BpE7?E&di~}5pS>{3 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zDEJKH^6VZq;rOm^jIKg-^1ll36Y(mzoU>a3tbkABUGc})*EZw>@Pz4D363&zDrijF zgKg3Q68(r@oul=r)t+-iH0W)QVq@Muu z{o51IDb~(OZR4&j3Yj;!!SW(fF}vv(`nOp3hdnv}Krg^UXVq;9?2>=^!6YwBmP7a> zN1s2CYkR`t6{Y9lAGjZ+gunj$Z>PWEzyAE+JP)iIdnWs`0B_%HFdad)yG{L}-1e_=;WQ}SP2eSM?Rayj+>U*vM?KPlAC9sZNDXnxg<|9|?% zOQ3mkfgYv;o0>p9LIs$Z-GFXw1#fF?)*oSZ6@=K)|Ib4o7Mu#>-)@@23iI#e03oN> z#mD$`jza|glLYR)2LnKt3t+oF1$C~9JqZ8ft2cedm6v@ce^rhDeJ`f7nquT4>$)PxSQ@GtSJ)SnyfZifdSOKm#2u8*RGJR@kwgF!)Fk@qg(^G2ZG20}U#-snqaORk zJ|1~N(YcQ4m~y;OiD$n;Y}cQ^G&S>>obzWTd>svQTVcjobm#gW@@JHIL5Cn+W6zq( zCa##r*o7X^RZJ9;`Tu8!$XBqr;Rdt7pz+Y3)UTJCo@iYcw>RriC1dpTKS$UBToM*G zpYA%eL5DLRI#fWym@Ezy str: else: return dicTerm -def is_valid_term(dicTerm): +def is_valid_term(dicTerm: str) -> bool: """ Check if a dictionary term is valid. - This function returns `True` if the term matches the regex pattern and `False` otherwise. + This functions returns True if the term matches the regex pattern and Flase otherwise. The regex pattern matches: - - - Alphanumeric characters (a-z, A-Z, 0-9) - - Valid symbols: `-`, `'`, `*`, `/` - - The `*` symbol can appear only once at the end of a word - - Emojis are valid only when they appear alone - - The `/` symbol can appear only once after alphanumeric characters + - Alphanumeric characters (a-zA-Z0-9) + - Valid symbols: -, ', *, / + - The * symbol can only appear once at the end of a word + - 8 emojis are valid only when they appear alone + - The / symbol can only appear once after alphanumeric characters - Spaces are allowed between valid words - :param dicTerm: The dictionary term to validate. + :param dicTerm: The dictionary term :type dicTerm: str - :return: `True` if the term is valid, `False` otherwise. + hi:) 120 + + :return: True/False :rtype: bool """ - - # List of emojis to preserve - emojis_to_preserve = { - "(:", "(;", "):", "/:", ":(", ":)", ":/", ";)" - } - emoji_pattern = '|'.join(re.escape(emoji) for emoji in emojis_to_preserve) + emoji_pattern = '|'.join(re.escape(emoji) for emoji in EMOJIS_TO_PRESERVE) alphanumeric_pattern = ( fr"^([a-zA-Z0-9\-']+(\*|\/[a-zA-Z0-9\*]*)?|({emoji_pattern})\*?)( [a-zA-Z0-9\-']+(\*|\/[a-zA-Z0-9\*]*)?)*$" ) return bool(re.match(alphanumeric_pattern, dicTerm)) +def sort_words(lexicons: list) -> str: + """ + Sorts the dictionary terms in a list. + + This function sorts the dictionary terms in a list by their length in descending order. + The hyphenated words are sorted first, followed by the non-hyphenated words. + + :param dicTerms: List of dictionary terms + :type dicTerms: list + + :return: dicTerms + :rtype: str + """ + hyphenated_words = [] + non_hyphenated_words = [] + for lexicon in lexicons: + lexicon = lexicon.strip() + lexicon = lexicon.replace("\n", "") + if lexicon == '': + continue + length = len(lexicon) + # no word boundaries for emojis + if any(emoji in lexicon for emoji in EMOJIS_TO_PRESERVE): + lexicon = lexicon.replace('(', r'\(').replace(')', r'\)') #.replace('/', r'\/') + else: + lexicon = lexicon.replace('(', r'\(').replace(')', r'\)') + word_boundaries = r"\b", r"\b" + if lexicon[-1] == "*": + pattern = re.compile(r'\*+') + lexicon = pattern.sub('*', lexicon) + if not lexicon[-2].isalnum(): + word_boundaries = r"(? dict: """ Loads up a dictionary that is in the LIWC 2007/2015 format. @@ -212,7 +243,18 @@ def load_liwc_dict(dicText: str) -> dict: This functions reads the content of a LIWC dictionary file in the official format, and convert it to a dictionary with lexicon: regular expression format. We assume the dicText has two parts: the header, which maps numbers to "category names," - and the body, which maps words in the lexicon to different category numbers, separated by a '%' sign. + and the body, which maps words in the lexicon to different category numbers, separated by '%'. + Below is an example: + ''' + % + 1 function + 2 pronoun + 3 ppron + % + again 1 2 + against 1 2 3 + ''' + Note that the elements in each line are separated by '\t'. :param dicText: The content of a .dic file :type dicText: str @@ -221,6 +263,9 @@ def load_liwc_dict(dicText: str) -> dict: :rtype: dict """ dicSplit = dicText.split('%', 2) + # check 2 '%' symbols + if len(dicSplit) != 3: + raise ValueError("Invalid dictionary file.") dicHeader, dicBody = dicSplit[1], dicSplit[2] # read headers catNameNumberMap = {} @@ -228,35 +273,35 @@ def load_liwc_dict(dicText: str) -> dict: if line.strip() == '': continue lineSplit = line.strip().split('\t') + # check header format: 1 function + if len(lineSplit) != 2 or not lineSplit[0].isdigit(): + raise ValueError("Invalid dictionary file.") catNameNumberMap[lineSplit[0]] = lineSplit[1] # read body dicCategories = {} for line in dicBody.splitlines(): lineSplit = line.strip().split('\t') - dicTerm, catNums = lineSplit[0], lineSplit[1:] - dicTerm = fix_abbreviations(dicTerm=' '.join(lineSplit[0].lower().strip().split())) - dicTerm = dicTerm.strip() - if dicTerm == '': + # check body format: again 1 2 + if lineSplit != [''] and len(lineSplit) < 2: continue - if not is_valid_term(dicTerm): - warnings.warn(f"WARNING: invalid dict term: {dicTerm}, skipped") - if '*' in dicTerm: - # Replace consecutive asterisks with a single asterisk -- e.g., '**'->'*' - pattern = re.compile(r'\*+') - dicTerm = pattern.sub('*', dicTerm) - dicTerm = r"\b" + dicTerm.replace("\n", "").replace("*", "") + r"\S*\b" - elif '(' in dicTerm or ')' in dicTerm or '/' in dicTerm: - dicTerm = dicTerm.replace("\n", "").replace('(', r'\(').replace(')', r'\)').replace('/', r'\/') - else: - dicTerm = r"\b" + dicTerm.replace("\n", "") + r"\b" - + lexicon, catNums = lineSplit[0], lineSplit[1:] + lexicon = fix_abbreviations(dicTerm=' '.join(lineSplit[0].lower().strip().split())) + lexicon = lexicon.strip() + if lexicon == '': + continue + if not is_valid_term(lexicon): + warnings.warn(f"WARNING: invalid lexicon: {lexicon}, skipped") + continue + for catNum in catNums: cat = catNameNumberMap[catNum] if cat not in dicCategories: - dicCategories[cat] = dicTerm + dicCategories[cat] = [lexicon] else: - cur_dicTerm = dicCategories[cat] - dicCategories[cat] = cur_dicTerm + "|" + dicTerm + dicCategories[cat].append(lexicon) + # sort the words in the dictionary + for cat, lexicons in dicCategories.items(): + dicCategories[cat] = sort_words(lexicons) return dicCategories def generate_certainty_pkl(): diff --git a/tests/data/cleaned_data/test_chat_level.csv b/tests/data/cleaned_data/test_chat_level.csv index f1efa901..2543d807 100644 --- a/tests/data/cleaned_data/test_chat_level.csv +++ b/tests/data/cleaned_data/test_chat_level.csv @@ -1,33 +1,33 @@ -conversation_num,speaker_nickname,message,expected_column,expected_value -1,A,Hello I like fish.,num_words,4 -1,B,This sentence has five words.,num_words,5 -2,A,Hello??,num_words,1 -2,A,1234,num_words,1 -2,B,Is 4 a word?,num_words,4 -3,A,.,num_words,0 -4,test_A,"HELLO WORLD, THIS IS A TEST. hi HI. hi HI hi HI""",num_all_caps,9 -4,test_B,ONE TWO THREE. four five six. sEvEn EiGhT nInE.,num_all_caps,3 -4,test_A,Check out this [link](https://example.com) and this one http://example.org,num_links,2 -4,test_B,I like google.com and wikipedia.org but not amazon.com,num_links,3 -4,test_A,why don't you read everything at https://www.example.com and https://www.example.org and https://www.example.net and https://www.example.ca and https://www.example.co.uk,num_links,5 +conversation_num,speaker_nickname,message,expected_column,expected_value +1,A,Hello I like fish.,num_words,4 +1,B,This sentence has five words.,num_words,5 +2,A,Hello??,num_words,1 +2,A,1234,num_words,1 +2,B,Is 4 a word?,num_words,4 +3,A,.,num_words,0 +4,test_A,"HELLO WORLD, THIS IS A TEST. hi HI. hi HI hi HI""",num_all_caps,9 +4,test_B,ONE TWO THREE. four five six. sEvEn EiGhT nInE.,num_all_caps,3 +4,test_A,Check out this [link](https://example.com) and this one http://example.org,num_links,2 +4,test_B,I like google.com and wikipedia.org but not amazon.com,num_links,3 +4,test_A,why don't you read everything at https://www.example.com and https://www.example.org and https://www.example.net and https://www.example.ca and https://www.example.co.uk,num_links,5 4,test_B,"why don't you read everything at - https://www.example.com - https://www.example.org - https://www.example.net - https://www.example.ca -- https://www.example.co.uk",num_links,5 -4,test_A,"Hello u/user1 and u/user2, hi hi hi?",num_reddit_users,2 -4,test_B,I don't like u/user_1_test but I like u/user2Test,num_reddit_users,2 -4,test_A,"This is **bold**, *italics*, and this is not. This is ***bolded and italicized***",num_emphasis,3 -4,test_B,This is **uneven* in terms of *the emphasis**,num_emphasis,2 -4,test_A,* item 1\n* item 2\n- item 3,num_bullet_points,3 +- https://www.example.co.uk",num_links,5 +4,test_A,"Hello u/user1 and u/user2, hi hi hi?",num_reddit_users,2 +4,test_B,I don't like u/user_1_test but I like u/user2Test,num_reddit_users,2 +4,test_A,"This is **bold**, *italics*, and this is not. This is ***bolded and italicized***",num_emphasis,3 +4,test_B,This is **uneven* in terms of *the emphasis**,num_emphasis,2 +4,test_A,* item 1\n* item 2\n- item 3,num_bullet_points,3 4,test_B,"Here are all my arguments: - point 1 - point 2 - point 3 -- point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines",num_bullet_points,4 -4,test_A,1. First\n2. Second\n3. Third,num_numbered_points,3 -4,test_B,This is the first line.\nThis is the second line.\nThis is the third line.,num_line_breaks,3 +- point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines point 4 is super long and takes up multiple lines",num_bullet_points,4 +4,test_A,1. First\n2. Second\n3. Third,num_numbered_points,3 +4,test_B,This is the first line.\nThis is the second line.\nThis is the third line.,num_line_breaks,3 4,test_A,"I have a line @@ -36,729 +36,1299 @@ conversation_num,speaker_nickname,message,expected_column,expected_value here is a new line -here is a third line",num_line_breaks,3 -4,test_B,this is a line with\rA different kind of return value\rUsing carriage return instead of the newline character,num_line_breaks,3 -4,test_A,"""This is a quote."" She said, ""Here's another.""",num_quotes,2 -4,test_B,"""You miss 100% of the shots you don't take"" -- Wayne Gretzky",num_quotes,1 -4,test_A,"""I can't believe you use single quotes to quote people,"" she said. ""Well, he replied, 'sometimes single quotes are useful when you nest quotes inside other quotes,' according to my English teacher"" Then she said: 'okay'",num_quotes,4 -4,test_B,> Quoting someone else\nThis is my reply.,num_block_quote_responses,1 -4,test_A,> Quoting someone else\nThis is my reply.,num_block_quote_responses,1 -4,test_B,>>>> This is a quote but I went overboard with the carat character,num_block_quote_responses,1 -4,test_A,>> This is one where I put too many of the gt's,num_block_quote_responses,1 +here is a third line",num_line_breaks,3 +4,test_B,this is a line with\rA different kind of return value\rUsing carriage return instead of the newline character,num_line_breaks,3 +4,test_A,"""This is a quote."" She said, ""Here's another.""",num_quotes,2 +4,test_B,"""You miss 100% of the shots you don't take"" -- Wayne Gretzky",num_quotes,1 +4,test_A,"""I can't believe you use single quotes to quote people,"" she said. ""Well, he replied, 'sometimes single quotes are useful when you nest quotes inside other quotes,' according to my English teacher"" Then she said: 'okay'",num_quotes,4 +4,test_B,> Quoting someone else\nThis is my reply.,num_block_quote_responses,1 +4,test_A,> Quoting someone else\nThis is my reply.,num_block_quote_responses,1 +4,test_B,>>>> This is a quote but I went overboard with the carat character,num_block_quote_responses,1 +4,test_A,>> This is one where I put too many of the gt's,num_block_quote_responses,1 4,test_B,"> Hello! -Goodbye!",num_block_quote_responses,1 +Goodbye!",num_block_quote_responses,1 4,test_B,"> here I am making a quote I respond to it > I quote again -I respond to that too",num_block_quote_responses,2 -4,test_A,Well... I'm not sure... Maybe...,num_ellipses,3 -4,test_B,hm..what if I only use two periods.............or many periods............,num_ellipses,2 -4,test_B,This is a sentence (with some text in parentheses).,num_parentheses,1 -4,test_A,"""Sure,"" I said confidently (thiking to myself: no way!) This was definitely (not) one of my best moments.",num_parentheses,2 -4,test_B,(((((these parentheses are not properly closed.),num_parentheses,1 -4,test_B,((there are multiple parentheses here)),num_parentheses,2 -4,test_A,((1+(1+3+4)^2)+7+(9+8)),num_parentheses,4 -5,test1,I think that I think that I think,certainty_rocklage,4.5 -5,test2,I am a little confused,certainty_rocklage,2.47 -5,test2,I don't really know the answer,certainty_rocklage,1.33 -5,test3,I am sure that this is correct,certainty_rocklage,8.02 -5,test1,I am fairly certain in my response,certainty_rocklage,8.28 -5,test2,This is without a doubt the best movie I have ever seen,certainty_rocklage,4.5 -5,test2,I am not sure about how to how to approximately handle this,certainty_rocklage,2.69 -5,test3,I believe that he is guilty but I am not very certain,certainty_rocklage,6.56 -5,test1,I an open to you changing my mind on this issue,certainty_rocklage,4.5 -5,test2,I don't think the guy is the a$$hole. Thoughts?,certainty_rocklage,5.44 -5,test2,So who thinks the guy is an ass for asking his mother in law to learn english,certainty_rocklage,4.5 -5,test3,"I think that this person is not an asshole because, according to him, he was very polite while approaching the issue",certainty_rocklage,6.037 -5,test1,I can see how the family is upset because they feel the mother was disrespected but I can also understand the guy's feelings. Why should he have to work as interpreter for his mother in law?,certainty_rocklage,4.5 -5,test2,"Yes, I think his feeling makes sense to me to. Who doesn't want to be independent.",certainty_rocklage,4.89 -5,test2,I was conflicted because I could understand his frustration however I feel he should have maybe discussed strategies with how to approach the mother in law with his wife first.,certainty_rocklage,4.684 -5,test3,His MIL has been here for 8 years. You would think she'd pick up some English by now.,certainty_rocklage,4.5 -5,test1,I think he had every right to want to help his mother in law,certainty_rocklage,4.28 -5,test2,I also agree with culturedCow,certainty_rocklage,4.5 -5,test2,"I don't think he's an asshole. I think his request is reasonable. If you go to live in a foreign country, you should learn the language.",certainty_rocklage,5.125 -5,test3,"I think the guy is an asshole because for all his talk about how easy it is to use resources to learn a language, he didn't take the time to research WHY some people do not.",certainty_rocklage,5.505 -5,test1,I think he also tried to utilize other resources such as language learning apps to help her learn,certainty_rocklage,4.28 -5,test2,"I think also he needs to understand that language learning is not the same for everyone, not everyone has the same capacity to learn new languages quickly.",certainty_rocklage,6.09 -5,test2,"Maybe she does have a problem with learning languages, but she could at least try.",certainty_rocklage,3.79 -5,test3,After the edit he done it made it sound like he really loves his family,certainty_rocklage,6.175 -5,test1,"I don't think the guy is wrong in asking her to learn more english being that she lives in America, but he has to understand she is older and may not have the patience or capacity to learn a lot of english.",certainty_rocklage,5.472 -5,test2,"Learning a second language is easiest when you're a child for a reason. Your brain is wired differently then, which makes it easier.",certainty_rocklage,5.4 -5,test2,I think he tried to help her.� He gave her resources to use and she apparently didn't use them.,certainty_rocklage,4.32 -1,A,hello,Hello_receptiveness_yeomans,1 -1,B,So how should we answer this,Token_count_receptiveness_yeomans,6 -1,A,We can start here. What is the question?,YesNo_Questions_receptiveness_yeomans,0 -1,B,I am not sure. Where is the rest of our team?,WH_Questions_receptiveness_yeomans,1 -1,B,"Please help me figure this out, I really want to do well on this please",Please_receptiveness_yeomans,2 -2,C,Hey,Hello_receptiveness_yeomans,1 -2,C,Okay bro lets split it 50/50,Impersonal_Pronoun_receptiveness_yeomans,1 -2,D,Maybe but how about 60/40? I doubt its fair otherwise,Hedges_receptiveness_yeomans,2 -2,C,Seems fair,Hedges_receptiveness_yeomans,1 -1,B,I am not sure. Where is the rest of our team?,First_Person_Single_receptiveness_yeomans,1 -1,B,"Well please help me figure this out, I really want to do well on this please okay",factuality_politeness_convokit,1 -2,C,Seems possible,hashedge_politeness_convokit,1 -2,E,I see what youre thinking but I disagree,Acknowledgement_receptiveness_yeomans,1 -2,E,We get only one chance so we should understand how to split it,Acknowledgement_receptiveness_yeomans,2 -2,D,"I just don't agree, I'm making the 60/40 split",Adverb_Limiter_receptiveness_yeomans,1 -3,G,hey,indirect_greeting_politeness_convokit,1 -3,G,I think we should try something else,1st_person_start_politeness_convokit,1 -3,F,Ok whatever. You should leave the team then,2nd_person_start_politeness_convokit,1 -4,H,Honestly thank you so so much,factuality_politeness_convokit,1 -4,H,What's the plan?,direct_question_politeness_convokit,1 -4,I,That is the dumbest idea I've heard; youre actually dumb af,hasnegative_politeness_convokit,1 -4,H,What's ur problem here?,hasnegative_politeness_convokit,1 -5,J,Pleasure and an honor to meet you all,haspositive_politeness_convokit,1 -5,K,We should try that next,haspositive_politeness_convokit,0 -5,J,Could you please explain why? I don't really understand why you are thinking that,subjunctive_politeness_convokit,1 -5,K,Sorry sorry I didn't mean to,apologizing_politeness_convokit,1 -6,L,I don't really want to work with you all but let's get this over with,Impersonal_Pronoun_receptiveness_yeomans,1 -6,J,Fine by me,Affirmation_receptiveness_yeomans,1 -6,K,Ok so which part should we do first? the first or second?,YesNo_Questions_receptiveness_yeomans,1 -7,L,Please don't do that?,please_start_politeness_convokit,1 -7,L,I don't think that will work,hashedge_politeness_convokit,1 -7,M,I'm exhuasted rn,hasnegative_politeness_convokit,0 -7,M,i don't really care please just finish this up,haspositive_politeness_convokit,0 -7,N,Please don't do that?,Please_receptiveness_yeomans,1 -7,N,I don't think that will work,Hedges_receptiveness_yeomans,0 -7,O,I'm exhuasted rn,Negative_Emotion_receptiveness_yeomans,0 -7,O,i don't really care please just finish this up,Positive_Emotion_receptiveness_yeomans,0 -8,P,i appreciate all this from you,gratitude_politeness_convokit,1 -8,P,"well we should start rn, our part is long",1st_person_pl_politeness_convokit,1 -8,Q,ok forgive me for this error but,apologizing_politeness_convokit,1 -8,Q,you have to redo the whole thing,2nd_person_politeness_convokit,0 -8,R,ok so who will work with me? where should we begin?,direct_question_politeness_convokit,0 -8,S,i appreciate all this from you,Gratitude_receptiveness_yeomans,1 -8,S,"well we should start rn, our part is long",First_Person_Plural_receptiveness_yeomans,2 -8,T,ok forgive us for this error but,Apology_receptiveness_yeomans,0 -8,T,you have to redo the whole thing,Second_Person_receptiveness_yeomans,1 -8,U,ok so who will work with me? where should we begin?,WH_Questions_receptiveness_yeomans,2 -9,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Impersonal_Pronoun_receptiveness_yeomans,12 -10,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",First_Person_Single_receptiveness_yeomans,5 -11,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Hedges_receptiveness_yeomans,3 -12,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Negation_receptiveness_yeomans,3 -13,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Subjectivity_receptiveness_yeomans,3 -14,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Negative_Emotion_receptiveness_yeomans,3 -15,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Reasoning_receptiveness_yeomans,1 -16,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Agreement_receptiveness_yeomans,1 -17,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Second_Person_receptiveness_yeomans,1 -18,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Adverb_Limiter_receptiveness_yeomans,1 -19,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Disagreement_receptiveness_yeomans,1 -20,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Acknowledgement_receptiveness_yeomans,1 -21,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",First_Person_Plural_receptiveness_yeomans,1 -22,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",For_Me_receptiveness_yeomans,0 -23,A,And I will always love you,Conjunction_Start_receptiveness_yeomans,1 -23,B,"Can you help me, can you please?",Can_You_receptiveness_yeomans,2 -23,C,"Can you, will you, could you please be mine?",Could_You_receptiveness_yeomans,1 -23,D,"This land is your land, this land is my land; this land was made for you and for me",For_You_receptiveness_yeomans,1 -0,0,unneccessagf shoulds shouldve should'nt,discrepancies_lexical_wordcount,4 -0,0,wouldnt unneedofek want must've should'nt,discrepancies_lexical_wordcount,5 -0,0,hopes wish,discrepancies_lexical_wordcount,2 -0,0,must'nt rather wouldn't ought'nt,discrepancies_lexical_wordcount,4 -0,0,needn't unwantpotnw hopefulness oughta couldn't,discrepancies_lexical_wordcount,5 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other,nltk_english_stopwords_lexical_wordcount,4 -0,0,probably,hedge_words_lexical_wordcount,1 -0,0,maybe I guess possibly sort of a little,hedge_words_lexical_wordcount,5 -0,0,a little possibly I think sort of probably,hedge_words_lexical_wordcount,5 -0,0,probably sort of,hedge_words_lexical_wordcount,2 -0,0,I think,hedge_words_lexical_wordcount,1 -0,0,I love dogs,positive_bert,0.932 -0,0,I love dogs!!!,positive_bert,0.980 -0,0,I love dogs,negative_bert,0.012 -0,0,I love dogs!!!,negative_bert,0.004 -0,0,This is relatively neutral,neutral_bert,0.470 -0,0,This is relatively neutral,positive_bert,0.505 -0,0,This is relatively neutral...,neutral_bert,0.492 -0,0,What the heck is going on,negative_bert,0.541 -0,0,What the heck is going on??,negative_bert,0.730 -0,0,!!!,positive_bert,0.917 -0,0,.,neutral_bert,0.577 -0,0,???,neutral_bert,0.713 -0,0,,num_chars,0 -0,0,a,num_chars,1 -0,0,ab,num_chars,2 -0,0,abc,num_chars,3 -0,0,abcd,num_chars,4 -0,0,abcde,num_chars,5 -0,0,abcdef,num_chars,6 -0,1,first,num_messages,1 -0,0,Who is this,num_question_naive,1 -0,0,Who is this. Why is this,num_question_naive,2 -0,0,Who what when where why is this,num_question_naive,1 -0,0,Who is this?,num_question_naive,1 -A,1,able am are,function_word_accommodation,0 -A,2,able am are hello,function_word_accommodation,3 -A,3,able am hello,function_word_accommodation,2 -A,2,able get got,function_word_accommodation,1 -A,5,get,function_word_accommodation,1 -B,1,able am are,content_word_accommodation,0 -B,2,able am are hello,content_word_accommodation,0 -B,3,able am hello yoyo,content_word_accommodation_per_conv,0.3333333 -B,2,hello yoyo,content_word_accommodation_per_conv,0.8333333 -C,1,i i i,first_pronouns_proportion,1 -C,2,i i taco taco,first_pronouns_proportion,0.5 -C,3,.,first_pronouns_proportion,0 -D,1,I went to the store,info_exchange_zscore_conversation,0 -D,2,Bought some groceries for dinner,info_exchange_zscore_conversation,1.2247 -D,3,It's raining today,info_exchange_zscore_conversation,-1.2247 -E,1,I sort of like this,hedge_naive,1 -E,2,I guess this is a little awesome,hedge_naive,1 -E,3,It's raining today,hedge_naive,0 -F,1,what??,NTRI,1 -F,3,sorry excuse me what's your name again?,NTRI,1 -F,1,huh?,NTRI,1 -F,3,pardon?,NTRI,1 -F,3,pardon,NTRI,0 -F,3,say what again?,NTRI,1 -F,3,say again?,NTRI,1 -F,3,say again,NTRI,1 -F,3,what's that?,NTRI,1 -F,3,what is that,NTRI,1 -F,2,this is not funny,NTRI,0 -G,1,what is going on,word_TTR,1 -G,3,what what,word_TTR,0.5 -G,2,what what is that,word_TTR,0.75 -H,1,fantastic difficulty,dale_chall_score,19.5257 -H,3,discover direction different,dale_chall_score,0.1488 -H,3,trying quote random,dale_chall_score,0.1488 -H,3,erase eraser errand every even dig dim dime dine computer,dale_chall_score,5.7115 -H,2,even this is magnificent!,dale_chall_score,7.7824 -H,4,even this is magnificent! even this is magnificent!,dale_chall_score,7.7824 -H,1,fantastic difficulty,dale_chall_classification,difficult -H,3,trying quote random,dale_chall_classification,easy -H,3,erase eraser errand every even dig dim dime dine computer,dale_chall_classification,medium -H,3,discover direction different,dale_chall_classification,easy -H,4,even this is magnificent! even this is magnificent!,dale_chall_classification,difficult -I,1,I am enjoying the weather today!,positivity_zscore_conversation,0.855868 -I,2,Likewise it's beautiful.,positivity_zscore_conversation,0.8156 -I,3,I'm not a fan of the rain.,positivity_zscore_conversation,-1.2577 -I,1,I think it's enchanting.,positivity_zscore_conversation,0.7766 -I,3,Agree to disagree.,positivity_zscore_conversation,-1.19044 -J,1,This conversation is more neutral.,positivity_zscore_conversation,-0.002217 -J,2,How are you doing?,positivity_zscore_conversation,-0.443621 -J,3,I am mainly studying today.,positivity_zscore_conversation,-0.704912 -J,1,Anything fun planned?,positivity_zscore_conversation,1.925224 -J,3,Mostly a trip to the library.,positivity_zscore_conversation,-0.774473 -K,1,This is the same text.,positivity_zscore_conversation, -K,1,This is the same text.,positivity_zscore_conversation, -K,1,This is the same text.,positivity_zscore_conversation, -K,1,This is the same text.,positivity_zscore_conversation, -K,1,This is the same text.,positivity_zscore_conversation, \ No newline at end of file +I respond to that too",num_block_quote_responses,2 +4,test_A,Well... I'm not sure... Maybe...,num_ellipses,3 +4,test_B,hm..what if I only use two periods.............or many periods............,num_ellipses,2 +4,test_B,This is a sentence (with some text in parentheses).,num_parentheses,1 +4,test_A,"""Sure,"" I said confidently (thiking to myself: no way!) This was definitely (not) one of my best moments.",num_parentheses,2 +4,test_B,(((((these parentheses are not properly closed.),num_parentheses,1 +4,test_B,((there are multiple parentheses here)),num_parentheses,2 +4,test_A,((1+(1+3+4)^2)+7+(9+8)),num_parentheses,4 +5,test1,I think that I think that I think,certainty_rocklage,4.5 +5,test2,I am a little confused,certainty_rocklage,2.47 +5,test2,I don't really know the answer,certainty_rocklage,1.33 +5,test3,I am sure that this is correct,certainty_rocklage,8.02 +5,test1,I am fairly certain in my response,certainty_rocklage,8.28 +5,test2,This is without a doubt the best movie I have ever seen,certainty_rocklage,4.5 +5,test2,I am not sure about how to how to approximately handle this,certainty_rocklage,2.69 +5,test3,I believe that he is guilty but I am not very certain,certainty_rocklage,6.56 +5,test1,I an open to you changing my mind on this issue,certainty_rocklage,4.5 +5,test2,I don't think the guy is the a$$hole. Thoughts?,certainty_rocklage,5.44 +5,test2,So who thinks the guy is an ass for asking his mother in law to learn english,certainty_rocklage,4.5 +5,test3,"I think that this person is not an asshole because, according to him, he was very polite while approaching the issue",certainty_rocklage,6.037 +5,test1,I can see how the family is upset because they feel the mother was disrespected but I can also understand the guy's feelings. Why should he have to work as interpreter for his mother in law?,certainty_rocklage,4.5 +5,test2,"Yes, I think his feeling makes sense to me to. Who doesn't want to be independent.",certainty_rocklage,4.89 +5,test2,I was conflicted because I could understand his frustration however I feel he should have maybe discussed strategies with how to approach the mother in law with his wife first.,certainty_rocklage,4.684 +5,test3,His MIL has been here for 8 years. You would think she'd pick up some English by now.,certainty_rocklage,4.5 +5,test1,I think he had every right to want to help his mother in law,certainty_rocklage,4.28 +5,test2,I also agree with culturedCow,certainty_rocklage,4.5 +5,test2,"I don't think he's an asshole. I think his request is reasonable. If you go to live in a foreign country, you should learn the language.",certainty_rocklage,5.125 +5,test3,"I think the guy is an asshole because for all his talk about how easy it is to use resources to learn a language, he didn't take the time to research WHY some people do not.",certainty_rocklage,5.505 +5,test1,I think he also tried to utilize other resources such as language learning apps to help her learn,certainty_rocklage,4.28 +5,test2,"I think also he needs to understand that language learning is not the same for everyone, not everyone has the same capacity to learn new languages quickly.",certainty_rocklage,6.09 +5,test2,"Maybe she does have a problem with learning languages, but she could at least try.",certainty_rocklage,3.79 +5,test3,After the edit he done it made it sound like he really loves his family,certainty_rocklage,6.175 +5,test1,"I don't think the guy is wrong in asking her to learn more english being that she lives in America, but he has to understand she is older and may not have the patience or capacity to learn a lot of english.",certainty_rocklage,5.472 +5,test2,"Learning a second language is easiest when you're a child for a reason. Your brain is wired differently then, which makes it easier.",certainty_rocklage,5.4 +5,test2,I think he tried to help her.� He gave her resources to use and she apparently didn't use them.,certainty_rocklage,4.32 +1,A,hello,Hello_receptiveness_yeomans,1 +1,B,So how should we answer this,Token_count_receptiveness_yeomans,6 +1,A,We can start here. What is the question?,YesNo_Questions_receptiveness_yeomans,0 +1,B,I am not sure. Where is the rest of our team?,WH_Questions_receptiveness_yeomans,1 +1,B,"Please help me figure this out, I really want to do well on this please",Please_receptiveness_yeomans,2 +2,C,Hey,Hello_receptiveness_yeomans,1 +2,C,Okay bro lets split it 50/50,Impersonal_Pronoun_receptiveness_yeomans,1 +2,D,Maybe but how about 60/40? I doubt its fair otherwise,Hedges_receptiveness_yeomans,2 +2,C,Seems fair,Hedges_receptiveness_yeomans,1 +1,B,I am not sure. Where is the rest of our team?,First_Person_Single_receptiveness_yeomans,1 +1,B,"Well please help me figure this out, I really want to do well on this please okay",factuality_politeness_convokit,1 +2,C,Seems possible,hashedge_politeness_convokit,1 +2,E,I see what youre thinking but I disagree,Acknowledgement_receptiveness_yeomans,1 +2,E,We get only one chance so we should understand how to split it,Acknowledgement_receptiveness_yeomans,2 +2,D,"I just don't agree, I'm making the 60/40 split",Adverb_Limiter_receptiveness_yeomans,1 +3,G,hey,indirect_greeting_politeness_convokit,1 +3,G,I think we should try something else,1st_person_start_politeness_convokit,1 +3,F,Ok whatever. You should leave the team then,2nd_person_start_politeness_convokit,1 +4,H,Honestly thank you so so much,factuality_politeness_convokit,1 +4,H,What's the plan?,direct_question_politeness_convokit,1 +4,I,That is the dumbest idea I've heard; youre actually dumb af,hasnegative_politeness_convokit,1 +4,H,What's ur problem here?,hasnegative_politeness_convokit,1 +5,J,Pleasure and an honor to meet you all,haspositive_politeness_convokit,1 +5,K,We should try that next,haspositive_politeness_convokit,0 +5,J,Could you please explain why? I don't really understand why you are thinking that,subjunctive_politeness_convokit,1 +5,K,Sorry sorry I didn't mean to,apologizing_politeness_convokit,1 +6,L,I don't really want to work with you all but let's get this over with,Impersonal_Pronoun_receptiveness_yeomans,1 +6,J,Fine by me,Affirmation_receptiveness_yeomans,1 +6,K,Ok so which part should we do first? the first or second?,YesNo_Questions_receptiveness_yeomans,1 +7,L,Please don't do that?,please_start_politeness_convokit,1 +7,L,I don't think that will work,hashedge_politeness_convokit,1 +7,M,I'm exhuasted rn,hasnegative_politeness_convokit,0 +7,M,i don't really care please just finish this up,haspositive_politeness_convokit,0 +7,N,Please don't do that?,Please_receptiveness_yeomans,1 +7,N,I don't think that will work,Hedges_receptiveness_yeomans,0 +7,O,I'm exhuasted rn,Negative_Emotion_receptiveness_yeomans,0 +7,O,i don't really care please just finish this up,Positive_Emotion_receptiveness_yeomans,0 +8,P,i appreciate all this from you,gratitude_politeness_convokit,1 +8,P,"well we should start rn, our part is long",1st_person_pl_politeness_convokit,1 +8,Q,ok forgive me for this error but,apologizing_politeness_convokit,1 +8,Q,you have to redo the whole thing,2nd_person_politeness_convokit,0 +8,R,ok so who will work with me? where should we begin?,direct_question_politeness_convokit,0 +8,S,i appreciate all this from you,Gratitude_receptiveness_yeomans,1 +8,S,"well we should start rn, our part is long",First_Person_Plural_receptiveness_yeomans,2 +8,T,ok forgive us for this error but,Apology_receptiveness_yeomans,0 +8,T,you have to redo the whole thing,Second_Person_receptiveness_yeomans,1 +8,U,ok so who will work with me? where should we begin?,WH_Questions_receptiveness_yeomans,2 +9,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Impersonal_Pronoun_receptiveness_yeomans,12 +10,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",First_Person_Single_receptiveness_yeomans,5 +11,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Hedges_receptiveness_yeomans,3 +12,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Negation_receptiveness_yeomans,3 +13,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Subjectivity_receptiveness_yeomans,3 +14,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Negative_Emotion_receptiveness_yeomans,3 +15,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Reasoning_receptiveness_yeomans,1 +16,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Agreement_receptiveness_yeomans,1 +17,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Second_Person_receptiveness_yeomans,1 +18,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Adverb_Limiter_receptiveness_yeomans,1 +19,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Disagreement_receptiveness_yeomans,1 +20,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",Acknowledgement_receptiveness_yeomans,1 +21,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",First_Person_Plural_receptiveness_yeomans,1 +22,A,"I understand your perspective and agree that I would not want to have resentment in the workplace against women, as that would further compound the issue we are looking at. I do think that it is true that women are underrepresented in STEM careers and am a believer that something should be done to address this discrepancy, even if that is not implementing a priority for women in hiring decisions. While I don\'t think that companies should explicitly hire simply because of their gender, I do think that they should be mindful of the gender gap in STEM and look to address those issues through their hiring practices.",For_Me_receptiveness_yeomans,0 +23,A,And I will always love you,Conjunction_Start_receptiveness_yeomans,1 +23,B,"Can you help me, can you please?",Can_You_receptiveness_yeomans,2 +23,C,"Can you, will you, could you please be mine?",Could_You_receptiveness_yeomans,1 +23,D,"This land is your land, this land is my land; this land was made for you and for me",For_You_receptiveness_yeomans,1 +0,0,I love dogs,positive_bert,0.932 +0,0,I love dogs!!!,positive_bert,0.980 +0,0,I love dogs,negative_bert,0.012 +0,0,I love dogs!!!,negative_bert,0.004 +0,0,This is relatively neutral,neutral_bert,0.470 +0,0,This is relatively neutral,positive_bert,0.505 +0,0,This is relatively neutral...,neutral_bert,0.492 +0,0,What the heck is going on,negative_bert,0.541 +0,0,What the heck is going on??,negative_bert,0.730 +0,0,!!!,positive_bert,0.917 +0,0,.,neutral_bert,0.577 +0,0,???,neutral_bert,0.713 +0,0,,num_chars,0 +0,0,a,num_chars,1 +0,0,ab,num_chars,2 +0,0,abc,num_chars,3 +0,0,abcd,num_chars,4 +0,0,abcde,num_chars,5 +0,0,abcdef,num_chars,6 +0,1,first,num_messages,1 +0,0,Who is this,num_question_naive,1 +0,0,Who is this. Why is this,num_question_naive,2 +0,0,Who what when where why is this,num_question_naive,1 +0,0,Who is this?,num_question_naive,1 +A,1,able am are,function_word_accommodation,0 +A,2,able am are hello,function_word_accommodation,3 +A,3,able am hello,function_word_accommodation,2 +A,2,able get got,function_word_accommodation,1 +A,5,get,function_word_accommodation,1 +B,1,able am are,content_word_accommodation,0 +B,2,able am are hello,content_word_accommodation,0 +B,3,able am hello yoyo,content_word_accommodation_per_conv,0.3333333 +B,2,hello yoyo,content_word_accommodation_per_conv,0.8333333 +C,1,i i i,first_pronouns_proportion,1 +C,2,i i taco taco,first_pronouns_proportion,0.5 +C,3,.,first_pronouns_proportion,0 +D,1,I went to the store,info_exchange_zscore_conversation,0 +D,2,Bought some groceries for dinner,info_exchange_zscore_conversation,1.2247 +D,3,It's raining today,info_exchange_zscore_conversation,-1.2247 +E,1,I sort of like this,hedge_naive,1 +E,2,I guess this is a little awesome,hedge_naive,1 +E,3,It's raining today,hedge_naive,0 +F,1,what??,NTRI,1 +F,3,sorry excuse me what's your name again?,NTRI,1 +F,1,huh?,NTRI,1 +F,3,pardon?,NTRI,1 +F,3,pardon,NTRI,0 +F,3,say what again?,NTRI,1 +F,3,say again?,NTRI,1 +F,3,say again,NTRI,1 +F,3,what's that?,NTRI,1 +F,3,what is that,NTRI,1 +F,2,this is not funny,NTRI,0 +G,1,what is going on,word_TTR,1 +G,3,what what,word_TTR,0.5 +G,2,what what is that,word_TTR,0.75 +H,1,fantastic difficulty,dale_chall_score,19.5257 +H,3,discover direction different,dale_chall_score,0.1488 +H,3,trying quote random,dale_chall_score,0.1488 +H,3,erase eraser errand every even dig dim dime dine computer,dale_chall_score,5.7115 +H,2,even this is magnificent!,dale_chall_score,7.7824 +H,4,even this is magnificent! even this is magnificent!,dale_chall_score,7.7824 +H,1,fantastic difficulty,dale_chall_classification,difficult +H,3,trying quote random,dale_chall_classification,easy +H,3,erase eraser errand every even dig dim dime dine computer,dale_chall_classification,medium +H,3,discover direction different,dale_chall_classification,easy +H,4,even this is magnificent! even this is magnificent!,dale_chall_classification,difficult +I,1,I am enjoying the weather today!,positivity_zscore_conversation,0.855868 +I,2,Likewise it's beautiful.,positivity_zscore_conversation,0.8156 +I,3,I'm not a fan of the rain.,positivity_zscore_conversation,-1.2577 +I,1,I think it's enchanting.,positivity_zscore_conversation,0.7766 +I,3,Agree to disagree.,positivity_zscore_conversation,-1.19044 +J,1,This conversation is more neutral.,positivity_zscore_conversation,-0.002217 +J,2,How are you doing?,positivity_zscore_conversation,-0.443621 +J,3,I am mainly studying today.,positivity_zscore_conversation,-0.704912 +J,1,Anything fun planned?,positivity_zscore_conversation,1.925224 +J,3,Mostly a trip to the library.,positivity_zscore_conversation,-0.774473 +K,1,This is the same text.,positivity_zscore_conversation, +K,1,This is the same text.,positivity_zscore_conversation, +K,1,This is the same text.,positivity_zscore_conversation, +K,1,This is the same text.,positivity_zscore_conversation, +K,1,This is the same text.,positivity_zscore_conversation, +1_discrepancies,discrepancies,"must( Lorem— ipsum- wishes; consectetur[ euismod# hoping¥ adipiscing£ tempor+ oughtnt% sed& tempor! wanted{ tempor"" euismod– oughtn't( euismod] consectetur> besides^ adipiscing/ consectetur¥ couldnt: ipsum^ expect( euismod£ undo+ consectetur£ consectetur! desir– tempor: consectetur/ yearn( Lorem[ outstanding¥ amet^ sed",discrepancies_lexical_wordcount,13 +1_hear,hear,"voic; dolor+ ipsum^ hears[ euismod- choir) Lorem# euismod| ringing[ dolor— shout' dolor? 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Lorem! pennies[ sed~ tempor,money_lexical_wordcount,13 +10_causation,causation,"trigger# euismod– tempor; change€ dolor< Lorem. intend# Lorem] depending( adipiscing{ Lorem; provok) sed£ dolor; how– amet¥ rational\ euismod"" generating€ adipiscing. sed= uses, ipsum? inferr) consectetur. tempor? affected¥ dolor] induc< adipiscing; affects$ consectetur) influenc: consectetur/ ipsum) caus+ euismod/ changes| adipiscing^ euismod/ origins( adipiscing= adipiscing# changing( euismod– boss"" euismod£ origin= ipsum~ solves/ consectetur# Lorem; founder... amet) euismod% permit% euismod? based^ consectetur¥ made) sed$ dolor' inact< tempor# coz> dolor] adipiscing, outcome) adipiscing< sed< hows, consectetur] generate– amet[ amet",causation_lexical_wordcount,30 +10_anger,anger,"annoy"" tempor> hating{ Lorem] dolor— dump/ sed| ludicrous¥ adipiscing' sucked... ipsum< vicious"" amet",anger_lexical_wordcount,6 +10_first_person_singular,first_person_singular,"ive> Lorem... ill{ sed] i' Lorem{ amet{ myself[ amet( ipsum^ Id"" tempor# tempor& my< adipiscing¥ Im: tempor. euismod: I've¥ Lorem: adipiscing> I'd: euismod> mine– tempor? amet= I'm# amet/ euismod} I'll- euismod",first_person_singular_lexical_wordcount,12 +10_feel,feel,"caress¥ amet? sed( hands"" ipsum& hand€ amet... sed} freez\ amet"" cold# amet% fuzz... consectetur- adipiscing: rubs€ tempor& amet$ leather% ipsum< thin$ Lorem, edging} tempor^ Lorem$ hard% dolor\ smooth^ sed- wet) tempor) consectetur",feel_lexical_wordcount,13 +10_tentativeness,tentativeness,"lots] ipsum' pretty# dolor/ depended€ adipiscing> tentativ# consectetur, allot~ Lorem^ lotof| Lorem– adipiscing^ overall# Lorem- disorient~ adipiscing— Lorem, depending\ adipiscing= sed€ unsure% dolor} amet¥ unclear— sed] ipsum£ appeared] euismod€ borderline£ consectetur. or; sed\ Lorem: guesses= ipsum– might've! Lorem| sed¥ hopefulness- sed{ usually> ipsum/ adipiscing& halfass¥ sed) amet¥ fairly; dolor( probable| Lorem... varies! tempor^ amet] mainly) dolor- unlikel– dolor. amet$ variab. euismod] tempor£ appearing$ ipsum\ anything< tempor",tentativeness_lexical_wordcount,27 +10_exclusive,exclusive,"or^ sed= dolor£ versus$ amet) something% dolor| just' tempor% whether! ipsum- not< consectetur^ if; euismod$ sometime] amet| but> tempor€ without, Lorem€ either\ tempor< amet[ except, euismod) really: amet| Lorem= unless{ amet) ipsum[ rather... amet> sed¥ vs+ dolor~ tempor",exclusive_lexical_wordcount,16 +10_verbs,verbs,being% sed– that'd– amet— consectetur... forgot$ sed[ ipsum] aint^ euismod,verbs_lexical_wordcount,4 +10_friends,friends,"buddies! consectetur} dolor; friend"" consectetur= neighbour/ euismod{ sed~ fiance) ipsum. mate– dolor( sweetie/ sed; roomate, consectetur' gf— tempor' amet£ girlfriend; Lorem> dolor& partner% adipiscing£ consectetur? soulmate— tempor",friends_lexical_wordcount,11 +10_article,article,alot{ ipsum[ tempor: a... adipiscing% the/ sed£ dolor,article_lexical_wordcount,3 +10_argue,argue,just— ipsum+ I know€ dolor! euismod? actually; sed{ and[ euismod% Lorem– so$ dolor- consectetur— but{ Lorem^ well¥ amet. adipiscing– because# euismod? really$ tempor( dolor( you know! adipiscing] consectetur< I believe] ipsum> u know^ sed! consectetur< oh] sed= Lorem— yes- amet,argue_lexical_wordcount,14 +10_auxiliary_verbs,auxiliary_verbs,"ought've' adipiscing} they're| dolor. ipsum: whod\ adipiscing- dolor& may€ adipiscing~ ought¥ dolor# amet= didn't= tempor( became£ euismod% becomes| adipiscing; dolor, theyre: amet~ tempor"" isnt& Lorem"" I'd; tempor= Lorem( you're) amet/ cannot} amet' youd= sed... wouldnt, sed> amet. couldnt% consectetur; euismod[ youve& Lorem! it's# adipiscing| euismod& heres¥ tempor< euismod> here's- ipsum' sed\ she'd: tempor[ could've; adipiscing€ thats' Lorem$ couldn't: amet; consectetur",auxiliary_verbs_lexical_wordcount,24 +10_cognitive_mech,cognitive_mech,"perceiv/ ipsum– adipiscing: analy^ consectetur"" ipsum% could£ Lorem! sorta€ euismod^ elicit£ dolor",cognitive_mech_lexical_wordcount,5 +10_preposition,preposition,"insides> amet! dolor( from. tempor! with& amet? ipsum. thru... Lorem: amet— in) consectetur( consectetur- of? euismod= inside& consectetur— up[ euismod. outside] tempor€ through= adipiscing€ under^ Lorem... beside} euismod] after: Lorem~ euismod= across; tempor£ euismod' for' amet& adipiscing[ off"" amet} over( Lorem~ euismod- besides^ Lorem~ sed> above| consectetur{ euismod} into= Lorem€ ipsum"" wanna& tempor] sed! behind? amet€ out& dolor^ consectetur: till: euismod£ euismod{ on' sed} underneath\ consectetur¥ to¥ consectetur/ adipiscing",preposition_lexical_wordcount,27 +10_first_person_plural,first_person_plural,"ourselves[ euismod... ours= tempor! adipiscing... lets$ adipiscing$ amet= we'd{ Lorem... we're, amet– ipsum{ us\ euismod¥ ipsum^ we... consectetur! tempor[ we've> euismod/ we'll£ euismod% weve% dolor= amet€ our# Lorem— adipiscing",first_person_plural_lexical_wordcount,11 +10_percept,percept,sweet$ amet^ sed> honey^ adipiscing+ leather' dolor+ amet€ flavour= tempor– Lorem/ sweetness# consectetur\ tempor{ fetid£ ipsum# dolor= reek# amet# Lorem' speech; tempor,percept_lexical_wordcount,8 +10_second_person,second_person,"you"" consectetur# ya} sed$ you'd€ sed¥ youll! ipsum, ipsum- you'll- tempor? amet( thou+ Lorem\ thee"" dolor"" youre– Lorem] tempor| thoust& Lorem! ye[ amet; you're{ dolor& amet. you've# dolor\ your— consectetur~ thine– consectetur^ yours! Lorem/ u; adipiscing| tempor",second_person_lexical_wordcount,16 +10_positive_words,positive_words,"altruistic— tempor"" tempor– reassure] euismod! flashy. sed£ brand-new... euismod^ euismod, record-setting, amet) divinely) Lorem! dolor"" sleek] sed",positive_words_lexical_wordcount,7 +10_first_person,first_person,"i€ sed€ my\ Lorem} euismod£ myself< tempor| ourselves~ sed( we( euismod£ ipsum: mine~ amet- tempor/ our, amet~ adipiscing",first_person_lexical_wordcount,7 +10_nltk_english_stopwords,nltk_english_stopwords,"there< consectetur^ you'll} dolor! dolor= s€ consectetur— ipsum( wouldn/ dolor= in] ipsum& don't& euismod( theirs– Lorem[ hadn– tempor€ tempor; the+ Lorem% over> adipiscing$ consectetur> only"" ipsum] consectetur",nltk_english_stopwords_lexical_wordcount,11 +10_hedge_words,hedge_words,sort of+ adipiscing} tempor£ a little> Lorem. probably= dolor€ I think£ ipsum( sed> maybe; dolor] ipsum. I guess~ ipsum... ipsum} kind of] euismod,hedge_words_lexical_wordcount,7 +1_mix,discrepancies,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",discrepancies_lexical_wordcount,0 +1_mix,hear,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",hear_lexical_wordcount,0 +1_mix,home,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",home_lexical_wordcount,0 +1_mix,conjunction,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",conjunction_lexical_wordcount,2 +1_mix,certainty,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",certainty_lexical_wordcount,2 +1_mix,inclusive,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",inclusive_lexical_wordcount,0 +1_mix,bio,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",bio_lexical_wordcount,3 +1_mix,achievement,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",achievement_lexical_wordcount,1 +1_mix,adverbs,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",adverbs_lexical_wordcount,0 +1_mix,anxiety,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",anxiety_lexical_wordcount,0 +1_mix,third_person,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",third_person_lexical_wordcount,1 +1_mix,negation,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",negation_lexical_wordcount,0 +1_mix,swear,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",swear_lexical_wordcount,1 +1_mix,death,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",death_lexical_wordcount,0 +1_mix,health,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",health_lexical_wordcount,1 +1_mix,see,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",see_lexical_wordcount,0 +1_mix,body,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",body_lexical_wordcount,0 +1_mix,family,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",family_lexical_wordcount,0 +1_mix,negative_affect,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",negative_affect_lexical_wordcount,1 +1_mix,quantifier,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",quantifier_lexical_wordcount,2 +1_mix,positive_affect,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",positive_affect_lexical_wordcount,7 +1_mix,insight,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",insight_lexical_wordcount,2 +1_mix,humans,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",humans_lexical_wordcount,0 +1_mix,present_tense,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",present_tense_lexical_wordcount,2 +1_mix,future_tense,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",future_tense_lexical_wordcount,1 +1_mix,past_tense,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",past_tense_lexical_wordcount,1 +1_mix,relative,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",relative_lexical_wordcount,3 +1_mix,sexual,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",sexual_lexical_wordcount,2 +1_mix,inhibition,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",inhibition_lexical_wordcount,1 +1_mix,sadness,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",sadness_lexical_wordcount,0 +1_mix,social,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",social_lexical_wordcount,4 +1_mix,indefinite_pronoun,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",indefinite_pronoun_lexical_wordcount,0 +1_mix,religion,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",religion_lexical_wordcount,0 +1_mix,work,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",work_lexical_wordcount,2 +1_mix,money,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",money_lexical_wordcount,1 +1_mix,causation,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",causation_lexical_wordcount,0 +1_mix,anger,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",anger_lexical_wordcount,0 +1_mix,first_person_singular,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",first_person_singular_lexical_wordcount,0 +1_mix,feel,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",feel_lexical_wordcount,0 +1_mix,tentativeness,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",tentativeness_lexical_wordcount,1 +1_mix,exclusive,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",exclusive_lexical_wordcount,1 +1_mix,verbs,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",verbs_lexical_wordcount,4 +1_mix,friends,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",friends_lexical_wordcount,0 +1_mix,article,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",article_lexical_wordcount,0 +1_mix,argue,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",argue_lexical_wordcount,1 +1_mix,auxiliary_verbs,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",auxiliary_verbs_lexical_wordcount,1 +1_mix,cognitive_mech,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",cognitive_mech_lexical_wordcount,6 +1_mix,preposition,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",preposition_lexical_wordcount,0 +1_mix,first_person_plural,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",first_person_plural_lexical_wordcount,0 +1_mix,percept,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",percept_lexical_wordcount,2 +1_mix,second_person,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",second_person_lexical_wordcount,0 +1_mix,positive_words,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",positive_words_lexical_wordcount,9 +1_mix,first_person,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",first_person_lexical_wordcount,0 +1_mix,nltk_english_stopwords,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",nltk_english_stopwords_lexical_wordcount,4 +1_mix,hedge_words,"then– tempor€ amet, upliftment] amet$ tempor, motherf€ Lorem[ Lorem; hire| adipiscing! disease¥ sed= knew} amet] consectetur; comes? Lorem? but~ Lorem— ipsum— tons– adipiscing< worst# consectetur' undeniab{ adipiscing# euismod"" lick£ tempor) sweet- euismod] wondering$ adipiscing. complain~ euismod< amet~ tehe' amet/ precise& ipsum$ Lorem( hug= ipsum& adipiscing} safe€ amet? loves; consectetur& staunch( amet$ ipsum+ she'll= amet¥ ipsum– top- dolor– madly< ipsum£ helpful~ Lorem= taxes$ consectetur( euismod",hedge_words_lexical_wordcount,0 +2_mix,discrepancies,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",discrepancies_lexical_wordcount,0 +2_mix,hear,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",hear_lexical_wordcount,0 +2_mix,home,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",home_lexical_wordcount,0 +2_mix,conjunction,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",conjunction_lexical_wordcount,0 +2_mix,certainty,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",certainty_lexical_wordcount,0 +2_mix,inclusive,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",inclusive_lexical_wordcount,1 +2_mix,bio,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",bio_lexical_wordcount,0 +2_mix,achievement,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",achievement_lexical_wordcount,0 +2_mix,adverbs,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",adverbs_lexical_wordcount,2 +2_mix,anxiety,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",anxiety_lexical_wordcount,0 +2_mix,third_person,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",third_person_lexical_wordcount,0 +2_mix,negation,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",negation_lexical_wordcount,0 +2_mix,swear,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",swear_lexical_wordcount,0 +2_mix,death,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",death_lexical_wordcount,0 +2_mix,health,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",health_lexical_wordcount,0 +2_mix,see,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",see_lexical_wordcount,0 +2_mix,body,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",body_lexical_wordcount,0 +2_mix,family,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",family_lexical_wordcount,0 +2_mix,negative_affect,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",negative_affect_lexical_wordcount,0 +2_mix,quantifier,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",quantifier_lexical_wordcount,0 +2_mix,positive_affect,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",positive_affect_lexical_wordcount,1 +2_mix,insight,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",insight_lexical_wordcount,0 +2_mix,humans,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",humans_lexical_wordcount,0 +2_mix,present_tense,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",present_tense_lexical_wordcount,0 +2_mix,future_tense,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",future_tense_lexical_wordcount,0 +2_mix,past_tense,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",past_tense_lexical_wordcount,1 +2_mix,relative,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",relative_lexical_wordcount,2 +2_mix,sexual,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",sexual_lexical_wordcount,0 +2_mix,inhibition,"around"" amet... d; consectetur} consectetur[ well-made= euismod- advocate& Lorem' transact~ euismod- rosary% consectetur",inhibition_lexical_wordcount,0 +2_mix,sadness,"around"" amet... d; 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Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",adverbs_lexical_wordcount,1 +3_mix,anxiety,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",anxiety_lexical_wordcount,1 +3_mix,third_person,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",third_person_lexical_wordcount,0 +3_mix,negation,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",negation_lexical_wordcount,1 +3_mix,swear,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",swear_lexical_wordcount,0 +3_mix,death,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",death_lexical_wordcount,0 +3_mix,health,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",health_lexical_wordcount,0 +3_mix,see,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",see_lexical_wordcount,0 +3_mix,body,"distract! ipsum. adipiscing? uphold, amet} clearly! 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Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",negative_affect_lexical_wordcount,4 +3_mix,quantifier,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",quantifier_lexical_wordcount,0 +3_mix,positive_affect,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",positive_affect_lexical_wordcount,1 +3_mix,insight,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",insight_lexical_wordcount,3 +3_mix,humans,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",humans_lexical_wordcount,1 +3_mix,present_tense,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",present_tense_lexical_wordcount,0 +3_mix,future_tense,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",future_tense_lexical_wordcount,1 +3_mix,past_tense,"distract! ipsum. adipiscing? uphold, amet} clearly! Lorem- enlighten) tempor\ snack– adipiscing? Lorem? arrival. consectetur( useless{ euismod& amet& champ– adipiscing? unsuccessful^ consectetur] ipsum~ defens? adipiscing^ shant+ tempor"" consectetur... dedicated) tempor| euismod( guy... consectetur( amet[ memor] Lorem[ consectetur| handier? sed} might've= euismod, euismod. source# consectetur: consectetur[ conclud> sed] grandchil, amet",past_tense_lexical_wordcount,0 +3_mix,relative,"distract! ipsum. adipiscing? uphold, amet} clearly! 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flourish+ ipsum} ICU< adipiscing# oldest' adipiscing! loved= ipsum# active"" sed- amet: scare# ipsum, heroic€ ipsum",present_tense_lexical_wordcount,1 +6_mix,future_tense,"redeeming; dolor< complie¥ consectetur( come... adipiscing% consectetur... got. ipsum! stayed> euismod% ipsum< incapab[ amet| explanat> adipiscing] amet, prove/ Lorem? amet— lady's£ euismod? tidy: euismod] taken{ consectetur; flourish+ ipsum} ICU< adipiscing# oldest' adipiscing! loved= ipsum# active"" sed- amet: scare# ipsum, heroic€ ipsum",future_tense_lexical_wordcount,0 +6_mix,past_tense,"redeeming; dolor< complie¥ consectetur( come... adipiscing% consectetur... got. ipsum! stayed> euismod% ipsum< incapab[ amet| explanat> adipiscing] amet, prove/ Lorem? amet— lady's£ euismod? tidy: euismod] taken{ consectetur; flourish+ ipsum} ICU< adipiscing# oldest' adipiscing! loved= ipsum# active"" sed- amet: scare# ipsum, heroic€ ipsum",past_tense_lexical_wordcount,4 +6_mix,relative,"redeeming; dolor< complie¥ consectetur( come... adipiscing% consectetur... got. ipsum! stayed> euismod% ipsum< incapab[ amet| explanat> adipiscing] amet, prove/ Lorem? amet— lady's£ euismod? tidy: euismod] taken{ consectetur; 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Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",inclusive_lexical_wordcount,0 +7_mix,bio,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",bio_lexical_wordcount,3 +7_mix,achievement,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! 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Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",adverbs_lexical_wordcount,0 +7_mix,anxiety,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",anxiety_lexical_wordcount,0 +7_mix,third_person,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",third_person_lexical_wordcount,0 +7_mix,negation,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",negation_lexical_wordcount,0 +7_mix,swear,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",swear_lexical_wordcount,1 +7_mix,death,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",death_lexical_wordcount,1 +7_mix,health,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",health_lexical_wordcount,1 +7_mix,see,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",see_lexical_wordcount,1 +7_mix,body,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",body_lexical_wordcount,2 +7_mix,family,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",family_lexical_wordcount,1 +7_mix,negative_affect,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",negative_affect_lexical_wordcount,0 +7_mix,quantifier,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",quantifier_lexical_wordcount,3 +7_mix,positive_affect,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",positive_affect_lexical_wordcount,6 +7_mix,insight,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",insight_lexical_wordcount,2 +7_mix,humans,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",humans_lexical_wordcount,0 +7_mix,present_tense,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",present_tense_lexical_wordcount,3 +7_mix,future_tense,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",future_tense_lexical_wordcount,0 +7_mix,past_tense,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",past_tense_lexical_wordcount,0 +7_mix,relative,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",relative_lexical_wordcount,4 +7_mix,sexual,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",sexual_lexical_wordcount,0 +7_mix,inhibition,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! Lorem\ fulfill; dolor? sucks[ consectetur^ lack$ euismod- euismod| succeeds[ adipiscing# courageous% adipiscing\ adipiscing+ info[ amet£ inflam: adipiscing+ adipiscing",inhibition_lexical_wordcount,0 +7_mix,sadness,"stepfat+ dolor{ griev} ipsum[ firstly^ tempor\ Lorem] lots] sed- crotch, euismod} hopeful[ dolor"" yay> sed] sed? sects, Lorem; fume~ tempor. lack> ipsum¥ practice€ consectetur] amet? applaud"" ipsum... consectetur< mop/ euismod< amet¥ peaceful< dolor) seems/ adipiscing¥ amet] nearest; Lorem"" suppose+ ipsum. problem-solver[ tempor. moment& sed: tempor, eye-catch— amet& adipiscing... graci+ consectetur! 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ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",discrepancies_lexical_wordcount,1 +10_mix,hear,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",hear_lexical_wordcount,0 +10_mix,home,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",home_lexical_wordcount,0 +10_mix,conjunction,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",conjunction_lexical_wordcount,0 +10_mix,certainty,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",certainty_lexical_wordcount,1 +10_mix,inclusive,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",inclusive_lexical_wordcount,0 +10_mix,bio,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",bio_lexical_wordcount,4 +10_mix,achievement,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",achievement_lexical_wordcount,0 +10_mix,adverbs,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",adverbs_lexical_wordcount,1 +10_mix,anxiety,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",anxiety_lexical_wordcount,0 +10_mix,third_person,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",third_person_lexical_wordcount,0 +10_mix,negation,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",negation_lexical_wordcount,2 +10_mix,swear,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",swear_lexical_wordcount,1 +10_mix,death,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",death_lexical_wordcount,0 +10_mix,health,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",health_lexical_wordcount,1 +10_mix,see,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",see_lexical_wordcount,0 +10_mix,body,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",body_lexical_wordcount,2 +10_mix,family,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",family_lexical_wordcount,0 +10_mix,negative_affect,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",negative_affect_lexical_wordcount,0 +10_mix,quantifier,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",quantifier_lexical_wordcount,1 +10_mix,positive_affect,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",positive_affect_lexical_wordcount,0 +10_mix,insight,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",insight_lexical_wordcount,3 +10_mix,humans,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",humans_lexical_wordcount,0 +10_mix,present_tense,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",present_tense_lexical_wordcount,4 +10_mix,future_tense,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",future_tense_lexical_wordcount,1 +10_mix,past_tense,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",past_tense_lexical_wordcount,2 +10_mix,relative,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",relative_lexical_wordcount,2 +10_mix,sexual,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",sexual_lexical_wordcount,1 +10_mix,inhibition,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",inhibition_lexical_wordcount,1 +10_mix,sadness,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",sadness_lexical_wordcount,0 +10_mix,social,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",social_lexical_wordcount,1 +10_mix,indefinite_pronoun,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",indefinite_pronoun_lexical_wordcount,0 +10_mix,religion,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",religion_lexical_wordcount,1 +10_mix,work,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",work_lexical_wordcount,0 +10_mix,money,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",money_lexical_wordcount,0 +10_mix,causation,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",causation_lexical_wordcount,1 +10_mix,anger,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",anger_lexical_wordcount,1 +10_mix,first_person_singular,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",first_person_singular_lexical_wordcount,0 +10_mix,feel,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",feel_lexical_wordcount,1 +10_mix,tentativeness,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",tentativeness_lexical_wordcount,3 +10_mix,exclusive,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",exclusive_lexical_wordcount,1 +10_mix,verbs,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",verbs_lexical_wordcount,9 +10_mix,friends,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",friends_lexical_wordcount,0 +10_mix,article,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",article_lexical_wordcount,0 +10_mix,argue,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",argue_lexical_wordcount,0 +10_mix,auxiliary_verbs,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",auxiliary_verbs_lexical_wordcount,5 +10_mix,cognitive_mech,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",cognitive_mech_lexical_wordcount,11 +10_mix,preposition,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",preposition_lexical_wordcount,2 +10_mix,first_person_plural,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",first_person_plural_lexical_wordcount,0 +10_mix,percept,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",percept_lexical_wordcount,1 +10_mix,second_person,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",second_person_lexical_wordcount,0 +10_mix,positive_words,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",positive_words_lexical_wordcount,5 +10_mix,first_person,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",first_person_lexical_wordcount,0 +10_mix,nltk_english_stopwords,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",nltk_english_stopwords_lexical_wordcount,5 +10_mix,hedge_words,"belief% sed— forgot{ euismod£ dolor/ couldn't¥ ipsum^ amet— affectation] Lorem> ipsum} drank^ Lorem) sed' forever[ amet/ mailed? euismod< sed? mightve[ dolor[ sed; affect' dolor> sed\ consistently' Lorem| euismod: may: tempor, colon( ipsum# xanax¥ dolor] cruel, amet... think– dolor< tempor, strikingly% euismod< cocks£ ipsum~ insides! ipsum. aren't- Lorem. sandy% adipiscing... consectetur) illuminating+ amet# steadiness= euismod¥ sed( except~ consectetur' tempor) most} adipiscing? here's"" tempor' dolor# understand; sed{ ipsum",hedge_words_lexical_wordcount,0 diff --git a/tests/ipython_notebooks/generate_liwc_tests_new.ipynb b/tests/ipython_notebooks/generate_liwc_tests_new.ipynb new file mode 100644 index 00000000..e78aa54e --- /dev/null +++ b/tests/ipython_notebooks/generate_liwc_tests_new.ipynb @@ -0,0 +1,360 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "import re\n", + "import pandas as pd\n", + "import random\n", + "import pickle\n", + "from pathlib import Path\n", + "from team_comm_tools.utils.check_embeddings import load_liwc_dict, sort_words\n", + "from team_comm_tools.features.lexical_features_v2 import get_liwc_count\n", + "from team_comm_tools import FeatureBuilder" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Functions" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "emojis_to_preserve = {\"(:\", \"(;\", \"):\", \"/:\", \":(\", \":)\", \":/\", \";)\"} \n", + "alphabet = [\"a\", \"b\", \"c\", \"d\", \"e\", \"f\", \"g\", \"h\", \"i\", \"j\", \"k\", \"l\", \"m\", \"n\", \"o\", \"p\", \"q\", \"r\", \"s\", \"t\", \"u\", \"v\", \"w\", \"x\", \"y\", \"z\"]\n", + "filler = [\"Lorem\", \"ipsum\", \"dolor\", \"amet\", \"consectetur\", \"adipiscing\", \"sed\", \"euismod\", \"tempor\"]\n", + "connectors = [\n", + " \",\", # Comma\n", + " \".\", # Period\n", + " \";\", # Semicolon\n", + " \":\", # Colon\n", + " \"-\", # Hyphen\n", + " \"–\", # En dash\n", + " \"—\", # Em dash\n", + " \"!\", # Exclamation mark\n", + " \"?\", # Question mark\n", + " \"(\", # Open parenthesis\n", + " \")\", # Close parenthesis\n", + " \"[\", # Open bracket\n", + " \"]\", # Close bracket\n", + " \"{\", # Open brace\n", + " \"}\", # Close brace\n", + " \"\\\"\", # Double quotation mark\n", + " \"'\", # Single quotation mark (apostrophe)\n", + " \"...\", # Ellipsis\n", + " \"/\", # Slash\n", + " \"\\\\\", # Backslash\n", + " \"|\", # Vertical bar (pipe)\n", + " \"+\", # Plus sign\n", + " \"=\", # Equal sign\n", + " \"<\", # Less than\n", + " \">\", # Greater than\n", + " # \"*\", # Asterisk\n", + " \"^\", # Caret\n", + " \"~\", # Tilde\n", + " \"$\", # Dollar sign\n", + " \"€\", # Euro sign\n", + " \"¥\", # Yen sign\n", + " \"£\", # Pound sign\n", + " \"#\", # Hash/Pound\n", + " \"&\", # Ampersand\n", + " \"%\", # Percent\n", + " # \"_\", # Underscore: doesn't work with word boundaries \\b\n", + "]\n", + "\n", + "def fill_wordlist(selected_words: list):\n", + " result = []\n", + " for word in selected_words:\n", + " word = word.strip()\n", + " # for strings in selected_words that end with *, append a random number of letters to that string\n", + " if word.endswith(\"*\"):\n", + " word = word[:-1] #+ ''.join(random.sample(alphabet, random.randint(1, 5)))\n", + " result.append(word)\n", + " # randomly add filler words\n", + " num_fillers = random.randint(1, 2)\n", + " fillers = random.choices(filler, k=num_fillers)\n", + " result.extend(fillers)\n", + " # randomly add connectors\n", + " output = \"\"\n", + " for i, word in enumerate(result):\n", + " output += word\n", + " if i < len(result) - 1: # Only add a connector if not the last word\n", + " output += random.choice(connectors)\n", + " output += \" \"\n", + "\n", + " return output\n", + "\n", + "def extract_words_from_regex(pattern):\n", + " words = []\n", + " # Remove word boundaries (\\b), negative lookbehind ((? Date: Fri, 20 Dec 2024 15:06:00 -0500 Subject: [PATCH 2/3] Small updates to documentation and adding .__version__ parameter (#332) * update examples hierarchy * Closes #318. * provide __version__ variable without setup.py * small fix --------- Co-authored-by: sundy1994 --- docs/build/doctrees/environment.pickle | Bin 335291 -> 335290 bytes docs/build/doctrees/examples.doctree | Bin 172293 -> 172295 bytes docs/build/html/_sources/examples.rst.txt | 38 +++++++-------- docs/build/html/examples.html | 54 +++++++++++----------- docs/build/html/index.html | 2 + docs/source/examples.rst | 38 +++++++-------- pyproject.toml | 6 +-- requirements.txt | 4 +- src/team_comm_tools/__init__.py | 5 +- 9 files changed, 79 insertions(+), 68 deletions(-) diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle index 73257e4f5430b2ac398dd38708008a7a590030b1..fede4ccd20053f02657dd331f88580059153c503 100644 GIT binary patch delta 22687 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Then, in your local environment, run the following: @@ -30,7 +31,7 @@ To use our tool, please ensure that you have Python >= 3.10 installed and a work This command will automatically install our package and all required dependencies. Troubleshooting ------------------ +================ In the event that some dependency installations fail (for example, you may get an error that ``en_core_web_sm`` from Spacy is not found, or that there is a missing NLTK resource), please run this simple one-line command in your terminal, which will force the installation of Spacy and NLTK dependencies: @@ -43,14 +44,14 @@ If you encounter a further issue in which the 'wordnet' package from NLTK is not You can also find a full list of our requirements `here `_. Import Recommendations: Virtual Environment and Pip ------------------------------------------------------ +===================================================== **We strongly recommend using a virtual environment in Python to run the package.** We have several specific dependency requirements. One important one is that we are currently only compatible with numpy < 2.0.0 because `numpy 2.0.0 and above `_ made significant changes that are not compatible with other dependencies of our package. As those dependencies are updated, we will support later versions of numpy. **We also strongly recommend that your version of pip is up-to-date (>=24.0).** There have been reports in which users have had trouble downloading dependencies (specifically, the Spacy package) with older versions of pip. If you get an error with downloading ``en_core_web_sm``, we recommend updating pip. Importing the Package ------------------------ +====================== After you import the package and install dependencies, you can then use our tool in your Python script as follows: @@ -62,13 +63,14 @@ Now you have access to the :ref:`feature_builder`. This is the main class that y *Note*: PyPI treats hyphens and underscores equally, so "pip install team_comm_tools" and "pip install team-comm-tools" are equivalent. However, Python does NOT treat them equally, and **you should use underscores when you import the package, like this: from team_comm_tools import FeatureBuilder**. +------------------------------------------------------- Walkthrough: Running the FeatureBuilder on Your Data -======================================================= +------------------------------------------------------- Next, we'll go through the details of running the FeatureBuilder on your data, discussing each of the specific options / parameters at your disposal. Configuring the FeatureBuilder --------------------------------- +================================ The FeatureBuilder accepts any Pandas DataFrame as the input, so you can read in data in whatever format you like. For the purposes of this walkthrough, we'll be using some jury deliberation data from `Hu et al. (2021) `_. @@ -97,10 +99,10 @@ Now we are ready to call the FeatureBuilder on our data. All we need to do is de jury_feature_builder.featurize() Basic Input Columns -~~~~~~~~~~~~~~~~~~~~ +--------------------- Conversation Parameters -************************** +~~~~~~~~~~~~~~~~~~~~~~~~~ * The **input_df** parameter is where you pass in your dataframe. In this case, we want to run the FeatureBuilder on the juries data that we read in! @@ -206,19 +208,19 @@ Turns Advanced Configuration Columns -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +------------------------------- More advanced users of the FeatureBuilder should consider the following optional parameters, depending on their needs. Regenerating Vector Cache -*************************** +~~~~~~~~~~~~~~~~~~~~~~~~~~ * The **regenerate_vectors** parameter controls whether you'd like the FeatureBuilder to re-generate the content in the **vector_directory**, even if we have already cached the output of a previous run. It is useful if the underlying data has changed, but you want to give the output file the same name as a previous run of the FeatureBuilder. * By default, **we assume that, if your output file is named the same, that the underlying vectors are the same**. If this isn't true, you should set **regenerate_vectors = True** in order to clear out the cache and re-generate the RoBERTa and SBERT outputs. Custom Features -***************** +~~~~~~~~~~~~~~~~~ * The **custom_features** parameter allows you to specify features that do not exist within our default set. **We default to NOT generating four features that depend on SBERT vectors, as the process for generating the vectors tends to be slow.** However, these features can provide interesting insights into the extent to which individuals in a conversation speak "similarly" or not, based on a vector similarity metric. To access these features, simply use the **custom_features** parameter: @@ -234,7 +236,7 @@ Custom Features * You can chose to add any of these features depending on your preference. Analyzing First Percentage (%) -******************************** +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ * The **analyze_first_pct** parameter allows you to "cut off" and separately analyze the first X% of a conversation, in case you wish to separately study different sections of a conversation as it progresses. For example, you may be interested in knowing how the attributes of the first 50% of a conversation differ from the attributes of the entire conversation. Then you can sepcify the following: @@ -247,14 +249,14 @@ Analyzing First Percentage (%) * By default, we will simply analyze 100% of each conversation. Named Entity Recognition -************************** +~~~~~~~~~~~~~~~~~~~~~~~~~~ * The parameters **ner_training_df** and **ner_cutoff** are required if you would like the FeatureBuilder to identify named entities in your conversations. For example, the sentence, "John, did you talk to Michael this morning?" has two named entities: "John" and "Michael." The FeatureBuilder includes a tool that automatically detects these named entities, but it requires the user (you!) to specify some training data with examples of the types of named entities you'd like to recognize. This is because proper nouns can take many forms, from standard Western-style names (e.g., "John") to pseudonymous online nicknames (like "littleHorse"). More information about these parameters can be found in :ref:`named_entity_recognition`. .. _custom_aggregation: Custom Aggregation -******************** +~~~~~~~~~~~~~~~~~~~ Imagine that you, as a researcher, are interested in high-level characteristics of the entire conversation (for example, how much is said), but you only have measures at the (lower) level of each individual utterance (for example, the number of words in each message). How would you "aggregate" information from the lower level to the higher level? @@ -317,7 +319,7 @@ The table below summarizes the different types of aggregation, and the ways in w Example Usage of Custom Aggregation Parameters -+++++++++++++++++++++++++++++++++++++++++++++++ +************************************************ To customize aggregation behavior, simply add the following when constructing your FeatureBuilder: @@ -336,14 +338,14 @@ To turn off aggregation, set the following parameters to ``False``. By default, user_aggregation = False Important Notes and Caveats -++++++++++++++++++++++++++++ +***************************** - **[NOTE 1]** Even when aggregation is disabled, totals of words, messages, and characters are still summarized, as these are required for calculating the Gini Coefficient features. - **[NOTE 2]** Be careful when choosing the "sum" aggregation method, as it is not always appropriate to use the "sum" as an aggregation function. While it is a sensible choice for utterance-level attributes that are *countable* (for example, the total number of words, or other lexical wordcounts), it is a less sensible choice for others (for example, it does not make sense to sum sentiment scores for each utterance in a conversation). Consequently, using the "sum" feature will come with an associated warning. - **[NOTE 3]** In addition to aggregating from the utterance (chat) level to the conversation level, we also aggregate from the speaker (user) level to the conversation level, using the same methods specified in ``convo_methods`` to do so. Cumulative Grouping -********************* +~~~~~~~~~~~~~~~~~~~~ * The parameters **cumulative_grouping** and **within_task** address a special case of having multiple conversational identifiers; **they assume that the same team has multiple sequential conversations, and that, in each conversation, they perform one or more separate activities**. This was originally created as a companion to a multi-stage Empirica game (see: ``_). For example, imagine that a team must complete 3 different tasks, each with 3 different subparts. Then we can model this event in terms of 1 team (High level), 3 tasks (Mid level), and 3 subparts per task (Low level). @@ -460,7 +462,7 @@ Here is some example output (for the RoBERTa sentiment feature): 'bert_sentiment_data': True} Feature Column Names -~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~ Once you call **.featurize()**, you can also obtain a convenient list of the feature columns generated by the toolkit: diff --git a/docs/build/html/examples.html b/docs/build/html/examples.html index 0efbca9c..075879bf 100644 --- a/docs/build/html/examples.html +++ b/docs/build/html/examples.html @@ -49,15 +49,17 @@

  • The Basics (Get Started Here!)
  • Worked Example
      -
    • Demo / Sample Code
        -
      • Getting Started
          -
        • Troubleshooting
          • -
        • Import Recommendations: Virtual Environment and Pip
          • -
        • Importing the Package
          • +
        • Demo / Sample Code
          • +
        • Getting Started
          • -
        • Walkthrough: Running the FeatureBuilder on Your Data
            -
          • Configuring the FeatureBuilder
            • +
          • Walkthrough: Running the FeatureBuilder on Your Data

            Finally, this page will walk you through a case study, highlighting top use cases and considerations when using the toolkit.

            +
            -

            Getting Started

            +

            Getting Started

            To use our tool, please ensure that you have Python >= 3.10 installed and a working version of pip, which is Python’s package installer. Then, in your local environment, run the following:

            pip install team_comm_tools

            This command will automatically install our package and all required dependencies.

            -

            Troubleshooting

            +

            Troubleshooting

            In the event that some dependency installations fail (for example, you may get an error that en_core_web_sm from Spacy is not found, or that there is a missing NLTK resource), please run this simple one-line command in your terminal, which will force the installation of Spacy and NLTK dependencies:

            download_resources
            @@ -124,12 +127,12 @@

            Troubleshootinghere.

            -

            Import Recommendations: Virtual Environment and Pip

            +

            Import Recommendations: Virtual Environment and Pip

            We strongly recommend using a virtual environment in Python to run the package. We have several specific dependency requirements. One important one is that we are currently only compatible with numpy < 2.0.0 because numpy 2.0.0 and above made significant changes that are not compatible with other dependencies of our package. As those dependencies are updated, we will support later versions of numpy.

            We also strongly recommend that your version of pip is up-to-date (>=24.0). There have been reports in which users have had trouble downloading dependencies (specifically, the Spacy package) with older versions of pip. If you get an error with downloading en_core_web_sm, we recommend updating pip.

            -

            Importing the Package

            +

            Importing the Package

            After you import the package and install dependencies, you can then use our tool in your Python script as follows:

            from team_comm_tools import FeatureBuilder
            @@ -139,10 +142,10 @@

            Importing the Package

            -

            Walkthrough: Running the FeatureBuilder on Your Data

            +

            Walkthrough: Running the FeatureBuilder on Your Data

            Next, we’ll go through the details of running the FeatureBuilder on your data, discussing each of the specific options / parameters at your disposal.

            -

            Configuring the FeatureBuilder

            +

            Configuring the FeatureBuilder

            The FeatureBuilder accepts any Pandas DataFrame as the input, so you can read in data in whatever format you like. For the purposes of this walkthrough, we’ll be using some jury deliberation data from Hu et al. (2021).

            We first import Pandas and read in the dataframe:

            import pandas as pd
@@ -164,9 +167,9 @@ 
            Configuring the FeatureBuilder
-
            Basic Input Columns
            
+
            Basic Input Columns
            
 
            
-
            Conversation Parameters
            
+
            Conversation Parameters
            
 
              
 
            • The input_df parameter is where you pass in your dataframe. In this case, we want to run the FeatureBuilder on the juries data that we read in!
              • 
 
            • The speaker_id_col refers to the name of the column containing a unique identifier for each speaker / participant in the conversation. Here, in the data, the name of our columns is called “speaker_nickname.”
              
@@ -207,7 +210,6 @@ 
              Conversation Parameters
 
              • 
 
            
-
            
 
            
 
            Vector Directory
            
 
              
@@ -284,11 +286,12 @@ 
              Turns
            +
            -
            Advanced Configuration Columns
            +

            Advanced Configuration Columns

            More advanced users of the FeatureBuilder should consider the following optional parameters, depending on their needs.

            -
            Regenerating Vector Cache
            +
            Regenerating Vector Cache

            • The regenerate_vectors parameter controls whether you’d like the FeatureBuilder to re-generate the content in the vector_directory, even if we have already cached the output of a previous run. It is useful if the underlying data has changed, but you want to give the output file the same name as a previous run of the FeatureBuilder.

              @@ -300,7 +303,7 @@
              Regenerating Vector Cache -
              Custom Features
              +
              Custom Features

              • The custom_features parameter allows you to specify features that do not exist within our default set. We default to NOT generating four features that depend on SBERT vectors, as the process for generating the vectors tends to be slow. However, these features can provide interesting insights into the extent to which individuals in a conversation speak “similarly” or not, based on a vector similarity metric. To access these features, simply use the custom_features parameter:

                @@ -321,7 +324,7 @@
                Custom Features -
                Analyzing First Percentage (%)
                +
                Analyzing First Percentage (%)

                • The analyze_first_pct parameter allows you to “cut off” and separately analyze the first X% of a conversation, in case you wish to separately study different sections of a conversation as it progresses. For example, you may be interested in knowing how the attributes of the first 50% of a conversation differ from the attributes of the entire conversation. Then you can sepcify the following:

                  @@ -337,13 +340,13 @@
                  Analyzing First Percentage (%) -
                  Named Entity Recognition
                  +
                  Named Entity Recognition

                  • The parameters ner_training_df and ner_cutoff are required if you would like the FeatureBuilder to identify named entities in your conversations. For example, the sentence, “John, did you talk to Michael this morning?” has two named entities: “John” and “Michael.” The FeatureBuilder includes a tool that automatically detects these named entities, but it requires the user (you!) to specify some training data with examples of the types of named entities you’d like to recognize. This is because proper nouns can take many forms, from standard Western-style names (e.g., “John”) to pseudonymous online nicknames (like “littleHorse”). More information about these parameters can be found in Named Entity Recognition.

            -
            Custom Aggregation
            +
            Custom Aggregation

            Imagine that you, as a researcher, are interested in high-level characteristics of the entire conversation (for example, how much is said), but you only have measures at the (lower) level of each individual utterance (for example, the number of words in each message). How would you “aggregate” information from the lower level to the higher level?

            A simple solution is to sum up to the total number of words per utterance, and group by the conversation identifier. Then, you would have the total number of words for the entire conversation. You can imagine doing similar aggregations for other types of statistics — for example, the average number of words, the variance in the number of words, and so on.

            The FeautureBuilder includes built-in functionality to perform aggregations across different levels of analysis. By default, all numeric attributes generated at the utterance (chat) level are aggregated using the functions mean, max, min, and stdev.

            @@ -415,7 +418,7 @@
            Named Entity Recognition -
            Example Usage of Custom Aggregation Parameters
            +
            Example Usage of Custom Aggregation Parameters

            To customize aggregation behavior, simply add the following when constructing your FeatureBuilder:

            convo_methods = ['max', 'median']  # This aggregates ONLY "positive_bert" at the conversation level using max and median.
 convo_columns = ['positive_bert'],
@@ -430,7 +433,7 @@ 
            Example Usage of Custom Aggregation Parameters
-
            Important Notes and Caveats
            
+
            Important Notes and Caveats
            
 
              
 
            • [NOTE 1] Even when aggregation is disabled, totals of words, messages, and characters are still summarized, as these are required for calculating the Gini Coefficient features.
              • 
 
            • [NOTE 2] Be careful when choosing the “sum” aggregation method, as it is not always appropriate to use the “sum” as an aggregation function. While it is a sensible choice for utterance-level attributes that are countable (for example, the total number of words, or other lexical wordcounts), it is a less sensible choice for others (for example, it does not make sense to sum sentiment scores for each utterance in a conversation). Consequently, using the “sum” feature will come with an associated warning.
              • 
@@ -439,7 +442,7 @@ 
              Important Notes and Caveats
-
              Cumulative Grouping
              
+
              Cumulative Grouping
              
 
                
 
              • The parameters cumulative_grouping and within_task address a special case of having multiple conversational identifiers; they assume that the same team has multiple sequential conversations, and that, in each conversation, they perform one or more separate activities. This was originally created as a companion to a multi-stage Empirica game (see: https://github.com/Watts-Lab/multi-task-empirica). For example, imagine that a team must complete 3 different tasks, each with 3 different subparts. Then we can model this event in terms of 1 team (High level), 3 tasks (Mid level), and 3 subparts per task (Low level).
                
 
                
@@ -504,7 +507,6 @@ 
                Cumulative Grouping
 
                Additional FeatureBuilder Considerations
                
 
                Here are some additional design details of the FeatureBuilder that you may wish to keep in mind:
                
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index bc64b98c..de04f500 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -215,6 +215,8 @@ 
                Table of ContentsWorked Example
 
                • 
 
              • Features: Technical Documentation
                  
diff --git a/docs/source/examples.rst b/docs/source/examples.rst
index d3c0c97f..e349c7d4 100644
--- a/docs/source/examples.rst
+++ b/docs/source/examples.rst
@@ -18,8 +18,9 @@ We also have demos available on Google Colab that you can copy and run on your o
 
 Finally, this page will walk you through a case study, highlighting top use cases and considerations when using the toolkit.
 
+----------------
 Getting Started
-=================
+----------------
 
 To use our tool, please ensure that you have Python >= 3.10 installed and a working version of `pip `_, which is Python's package installer. Then, in your local environment, run the following:
 
@@ -30,7 +31,7 @@ To use our tool, please ensure that you have Python >= 3.10 installed and a work
 This command will automatically install our package and all required dependencies.
 
 Troubleshooting
------------------
+================
 
 In the event that some dependency installations fail (for example, you may get an error that ``en_core_web_sm`` from Spacy is not found, or that there is a missing NLTK resource), please run this simple one-line command in your terminal, which will force the installation of Spacy and NLTK dependencies:
 
@@ -43,14 +44,14 @@ If you encounter a further issue in which the 'wordnet' package from NLTK is not
 You can also find a full list of our requirements `here `_.
 
 Import Recommendations: Virtual Environment and Pip
------------------------------------------------------
+=====================================================
 
 **We strongly recommend using a virtual environment in Python to run the package.** We have several specific dependency requirements. One important one is that we are currently only compatible with numpy < 2.0.0 because `numpy 2.0.0 and above `_ made significant changes that are not compatible with other dependencies of our package. As those dependencies are updated, we will support later versions of numpy.
 
 **We also strongly recommend that your version of pip is up-to-date (>=24.0).** There have been reports in which users have had trouble downloading dependencies (specifically, the Spacy package) with older versions of pip. If you get an error with downloading ``en_core_web_sm``, we recommend updating pip.
 
 Importing the Package
------------------------
+======================
 
 After you import the package and install dependencies, you can then use our tool in your Python script as follows:
 
@@ -62,13 +63,14 @@ Now you have access to the :ref:`feature_builder`. This is the main class that y
 
 *Note*: PyPI treats hyphens and underscores equally, so "pip install team_comm_tools" and "pip install team-comm-tools" are equivalent. However, Python does NOT treat them equally, and **you should use underscores when you import the package, like this: from team_comm_tools import FeatureBuilder**.
 
+-------------------------------------------------------
 Walkthrough: Running the FeatureBuilder on Your Data
-=======================================================
+-------------------------------------------------------
 
 Next, we'll go through the details of running the FeatureBuilder on your data, discussing each of the specific options / parameters at your disposal.
 
 Configuring the FeatureBuilder
---------------------------------
+================================
 
 The FeatureBuilder accepts any Pandas DataFrame as the input, so you can read in data in whatever format you like. For the purposes of this walkthrough, we'll be using some jury deliberation data from `Hu et al. (2021) `_. 
 
@@ -97,10 +99,10 @@ Now we are ready to call the FeatureBuilder on our data. All we need to do is de
 	jury_feature_builder.featurize()
 
 Basic Input Columns
-~~~~~~~~~~~~~~~~~~~~
+---------------------
 
 Conversation Parameters
-**************************
+~~~~~~~~~~~~~~~~~~~~~~~~~
 
 * The **input_df** parameter is where you pass in your dataframe. In this case, we want to run the FeatureBuilder on the juries data that we read in!
 
@@ -206,19 +208,19 @@ Turns
 
 
 Advanced Configuration Columns
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+-------------------------------
 
 More advanced users of the FeatureBuilder should consider the following optional parameters, depending on their needs.
 
 Regenerating Vector Cache
-***************************
+~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 * The **regenerate_vectors** parameter controls whether you'd like the FeatureBuilder to re-generate the content in the **vector_directory**, even if we have already cached the output of a previous run. It is useful if the underlying data has changed, but you want to give the output file the same name as a previous run of the FeatureBuilder.
 
 	* By default, **we assume that, if your output file is named the same, that the underlying vectors are the same**. If this isn't true, you should set **regenerate_vectors = True** in order to clear out the cache and re-generate the RoBERTa and SBERT outputs.
 
 Custom Features
-*****************
+~~~~~~~~~~~~~~~~~
 
 * The **custom_features** parameter allows you to specify features that do not exist within our default set. **We default to NOT generating four features that depend on SBERT vectors, as the process for generating the vectors tends to be slow.** However, these features can provide interesting insights into the extent to which individuals in a conversation speak "similarly" or not, based on a vector similarity metric. To access these features, simply use the **custom_features** parameter:
 
@@ -234,7 +236,7 @@ Custom Features
     * You can chose to add any of these features depending on your preference.
 
 Analyzing First Percentage (%)
-********************************
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 * The **analyze_first_pct** parameter allows you to "cut off" and separately analyze the first X% of a conversation, in case you wish to separately study different sections of a conversation as it progresses. For example, you may be interested in knowing how the attributes of the first 50% of a conversation differ from the attributes of the entire conversation. Then you can sepcify the following:
 
@@ -247,14 +249,14 @@ Analyzing First Percentage (%)
 	* By default, we will simply analyze 100% of each conversation.
 
 Named Entity Recognition
-**************************
+~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 * The parameters **ner_training_df** and **ner_cutoff** are required if you would like the FeatureBuilder to identify named entities in your conversations. For example, the sentence, "John, did you talk to Michael this morning?" has two named entities: "John" and "Michael." The FeatureBuilder includes a tool that automatically detects these named entities, but it requires the user (you!) to specify some training data with examples of the types of named entities you'd like to recognize. This is because proper nouns can take many forms, from standard Western-style names (e.g., "John") to pseudonymous online nicknames (like "littleHorse"). More information about these parameters can be found in :ref:`named_entity_recognition`.
 
 .. _custom_aggregation:
 
 Custom Aggregation
-********************
+~~~~~~~~~~~~~~~~~~~
 
 Imagine that you, as a researcher, are interested in high-level characteristics of the entire conversation (for example, how much is said), but you only have measures at the (lower) level of each individual utterance (for example, the number of words in each message). How would you "aggregate" information from the lower level to the higher level?
 
@@ -317,7 +319,7 @@ The table below summarizes the different types of aggregation, and the ways in w
 
 
 Example Usage of Custom Aggregation Parameters
-+++++++++++++++++++++++++++++++++++++++++++++++
+************************************************
 
 To customize aggregation behavior, simply add the following when constructing your FeatureBuilder:
 
@@ -336,14 +338,14 @@ To turn off aggregation, set the following parameters to ``False``. By default,
      user_aggregation = False
 
 Important Notes and Caveats
-++++++++++++++++++++++++++++
+*****************************
 
 - **[NOTE 1]** Even when aggregation is disabled, totals of words, messages, and characters are still summarized, as these are required for calculating the Gini Coefficient features.
 - **[NOTE 2]** Be careful when choosing the "sum" aggregation method, as it is not always appropriate to use the "sum" as an aggregation function. While it is a sensible choice for utterance-level attributes that are *countable* (for example, the total number of words, or other lexical wordcounts), it is a less sensible choice for others (for example, it does not make sense to sum sentiment scores for each utterance in a conversation). Consequently, using the "sum" feature will come with an associated warning.
 - **[NOTE 3]** In addition to aggregating from the utterance (chat) level to the conversation level, we also aggregate from the speaker (user) level to the conversation level, using the same methods specified in ``convo_methods`` to do so.
 
 Cumulative Grouping
-*********************
+~~~~~~~~~~~~~~~~~~~~
 
 * The parameters **cumulative_grouping** and **within_task** address a special case of having multiple conversational identifiers; **they assume that the same team has multiple sequential conversations, and that, in each conversation, they perform one or more separate activities**. This was originally created as a companion to a multi-stage Empirica game (see: ``_). For example, imagine that a team must complete 3 different tasks, each with 3 different subparts. Then we can model this event in terms of 1 team (High level), 3 tasks (Mid level), and 3 subparts per task (Low level).
 
@@ -460,7 +462,7 @@ Here is some example output (for the RoBERTa sentiment feature):
 	 'bert_sentiment_data': True}
 
 Feature Column Names
-~~~~~~~~~~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~
 
 Once you call **.featurize()**, you can also obtain a convenient list of the feature columns generated by the toolkit:
 
diff --git a/pyproject.toml b/pyproject.toml
index 7a8ab6a4..a4cb44e8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [build-system]
 requires = [
-  "setuptools >= 42", "wheel"
+  "setuptools >= 42", "wheel", "toml"
 ]
 build-backend = "setuptools.build_meta"
 
@@ -13,6 +13,7 @@ dependencies = [
   "convokit==3.0.0",
   "emoji==1.7.0",
   "flask==3.0.3",
+  "fuzzywuzzy==0.18.0",
   "gensim>=4.3.3",
   "matplotlib>=3.0.0",
   "nltk==3.9.1",
@@ -39,8 +40,7 @@ dependencies = [
   "transformers==4.44.0",
   "tqdm>=4.66.5",
   "tzdata>=2023.3",
-  "tzlocal==5.2",
-  "fuzzywuzzy==0.18.0"
+  "tzlocal==5.2"
 ]
 authors = [
   {name = "Xinlan Emily Hu", email = "xehu@wharton.upenn.edu"},
diff --git a/requirements.txt b/requirements.txt
index c99c5fdd..f2593f54 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,6 +2,7 @@ chardet>=3.0.4
 convokit==3.0.0
 emoji==1.7.0
 flask==3.0.3
+fuzzywuzzy==0.18.0
 gensim>=4.3.3
 matplotlib>=3.0.0
 nltk==3.9.1
@@ -28,5 +29,4 @@ torchvision==0.19.1
 transformers==4.44.0
 tqdm>=4.66.5
 tzdata>=2023.3
-tzlocal==5.2
-fuzzywuzzy==0.18.0
\ No newline at end of file
+tzlocal==5.2
\ No newline at end of file
diff --git a/src/team_comm_tools/__init__.py b/src/team_comm_tools/__init__.py
index ab0556ea..0ad8d062 100644
--- a/src/team_comm_tools/__init__.py
+++ b/src/team_comm_tools/__init__.py
@@ -1 +1,4 @@
-from .feature_builder import FeatureBuilder
\ No newline at end of file
+from .feature_builder import FeatureBuilder
+from importlib.metadata import version as get_version
+
+__version__ = get_version("team_comm_tools")
\ No newline at end of file

From 009d33e2e7ab70d622d741bb5b6eacfbe841cfd2 Mon Sep 17 00:00:00 2001
From: sundy1994 
Date: Fri, 20 Dec 2024 15:33:44 -0800
Subject: [PATCH 3/3] update docs in liwc.rst and build again

---
 docs/build/doctrees/environment.pickle        | Bin 335290 -> 311257 bytes
 docs/build/doctrees/examples.doctree          | Bin 172295 -> 172286 bytes
 docs/build/doctrees/feature_builder.doctree   | Bin 107321 -> 2987 bytes
 .../doctrees/features/basic_features.doctree  | Bin 13636 -> 13564 bytes
 .../doctrees/features/burstiness.doctree      | Bin 15930 -> 15876 bytes
 .../build/doctrees/features/certainty.doctree | Bin 9167 -> 9131 bytes
 .../features/discursive_diversity.doctree     | Bin 15684 -> 15612 bytes
 docs/build/doctrees/features/fflow.doctree    | Bin 9248 -> 9212 bytes
 .../features/get_all_DD_features.doctree      | Bin 15053 -> 14999 bytes
 .../features/get_user_network.doctree         | Bin 14401 -> 14347 bytes
 docs/build/doctrees/features/hedge.doctree    | Bin 7693 -> 7657 bytes
 docs/build/doctrees/features/index.doctree    | Bin 13221 -> 13212 bytes
 .../features/info_exchange_zscore.doctree     | Bin 11803 -> 11767 bytes
 .../features/information_diversity.doctree    | Bin 24856 -> 24766 bytes
 .../features/lexical_features_v2.doctree      | Bin 17930 -> 17867 bytes
 .../named_entity_recognition_features.doctree | Bin 28281 -> 28173 bytes
 .../features/other_lexical_features.doctree   | Bin 16430 -> 16358 bytes
 .../features/politeness_features.doctree      | Bin 8006 -> 7970 bytes
 .../doctrees/features/politeness_v2.doctree   | Bin 8719 -> 8683 bytes
 .../features/politeness_v2_helper.doctree     | Bin 97129 -> 96697 bytes
 .../doctrees/features/question_num.doctree    | Bin 8828 -> 8792 bytes
 .../doctrees/features/readability.doctree     | Bin 20675 -> 20594 bytes
 .../doctrees/features/reddit_tags.doctree     | Bin 45337 -> 45103 bytes
 .../features/temporal_features.doctree        | Bin 22179 -> 22107 bytes
 .../textblob_sentiment_analysis.doctree       | Bin 13504 -> 13450 bytes
 .../features/turn_taking_features.doctree     | Bin 18984 -> 18912 bytes
 .../doctrees/features/variance_in_DD.doctree  | Bin 5051 -> 5024 bytes
 .../within_person_discursive_range.doctree    | Bin 6755 -> 6719 bytes
 .../doctrees/features/word_mimicry.doctree    | Bin 60853 -> 60637 bytes
 .../features_conceptual/TEMPLATE.doctree      | Bin 9294 -> 9285 bytes
 .../content_word_accommodation.doctree        | Bin 26456 -> 26447 bytes
 .../function_word_accommodation.doctree       | Bin 19960 -> 19951 bytes
 .../features_conceptual/index.doctree         | Bin 6627 -> 6618 bytes
 .../features_conceptual/mimicry_bert.doctree  | Bin 14372 -> 14363 bytes
 .../moving_mimicry.doctree                    | Bin 13876 -> 13867 bytes
 .../named_entity_recognition.doctree          | Bin 17880 -> 17871 bytes
 .../positivity_bert.doctree                   | Bin 13960 -> 13951 bytes
 .../turn_taking_index.doctree                 | Bin 16151 -> 16142 bytes
 .../features_conceptual/word_ttr.doctree      | Bin 8548 -> 8539 bytes
 docs/build/doctrees/index.doctree             | Bin 29743 -> 29734 bytes
 docs/build/doctrees/intro.doctree             | Bin 34402 -> 34393 bytes
 .../doctrees/utils/assign_chunk_nums.doctree  | Bin 30069 -> 29979 bytes
 .../calculate_chat_level_features.doctree     | Bin 92190 -> 91803 bytes
 ...culate_conversation_level_features.doctree | Bin 59447 -> 3123 bytes
 .../calculate_user_level_features.doctree     | Bin 38253 -> 3083 bytes
 .../doctrees/utils/check_embeddings.doctree   | Bin 69957 -> 73527 bytes
 .../doctrees/utils/gini_coefficient.doctree   | Bin 13770 -> 13716 bytes
 docs/build/doctrees/utils/index.doctree       | Bin 8887 -> 8878 bytes
 .../doctrees/utils/preload_word_lists.doctree | Bin 14062 -> 13972 bytes
 docs/build/doctrees/utils/preprocess.doctree  | Bin 55450 -> 55288 bytes
 .../doctrees/utils/summarize_features.doctree | Bin 93593 -> 93359 bytes
 .../zscore_chats_and_conversation.doctree     | Bin 15919 -> 15865 bytes
 docs/build/html/feature_builder.html          | 258 +-----------------
 docs/build/html/genindex.html                 |  93 +------
 docs/build/html/index.html                    |   5 +-
 docs/build/html/objects.inv                   | Bin 4466 -> 4221 bytes
 docs/build/html/py-modindex.html              |  15 -
 docs/build/html/searchindex.js                |   2 +-
 ...calculate_conversation_level_features.html | 182 +-----------
 .../utils/calculate_user_level_features.html  | 111 +-------
 docs/build/html/utils/check_embeddings.html   |  66 +++--
 docs/source/features_conceptual/liwc.rst      |   8 +
 62 files changed, 76 insertions(+), 664 deletions(-)

diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle
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zp)eMbbpc(Qu~}I>n$w`4MEgMgoSd)1wOK}SKNDHHH|MLI<1=U`-QJMRr;Mu@0XEsQ
AnE(I)

delta 570
zcmey9c_fRqfpw~-=|Vw}XC+_v6E0ODgMM=CUZ5hm
bdAV!}8(F$HFHl)3Zct64y_@T7_AmkfOh$}B

delta 412
zcmZpv*;T{Zz&cgmZX;_jqh*YKXmM&$v3^BrMyb9_YH@Z+et~{SYGSTJKv8~jYH_iG
zZ(>0~W?s5}2~aRTIX^cyz9c_Cr+9M*;{+zlesZ->F5rsUyo6;AEBQujF5s#YvYbJI
i3w$?c%l5EQX2j%dS&7X(Dm~(sEfl!KXY&-B0!9F8X`1E$

diff --git a/docs/build/doctrees/features/certainty.doctree b/docs/build/doctrees/features/certainty.doctree
index 5f729c1178c26aed9dd88870dcec337f9ee2f6f2..c7c3985e81841f49315fecd2779bd51a1f2411e1 100644
GIT binary patch
delta 241
zcmX@_zS^CofpzMFjVwWo20{9v#i>Qb`jw>>rHOe}8Tu~y$)&lec_qdA&iN^+`X#A}
zxw-{K`N^rp#k#qP1)KXByO<2xNz^r2Ude0o9G2_MWa*qdhedcZC+A%WgGv(Z-7K%P
Gfe`?}!CDmn

delta 273
zcmZ4Oe%_s>fpzMUjVwWomeKm5#i>Qb`W2}erTQ+Z#n~nK1^OYWiMa{^Mfu68#l;G~
zi3J6jdFlEkK*9Lr{M_95lKlLf;>~T0T}+k}$kjf1B1i1zxhzMR$v0y2L=G!S%O(n3
L;I-LRDUA^T6G~?2

diff --git a/docs/build/doctrees/features/discursive_diversity.doctree b/docs/build/doctrees/features/discursive_diversity.doctree
index bde9cf9acb84d5a2053f9446757b4d9e8b3b7470..94028c977b203f0cd7c12d99f66e53c204da7454 100644
GIT binary patch
delta 466
zcmX?7^{0}xfpzLfn~kiQj0Um#p~b01#rl<{6{U%JRT=s&`N^fZsd**E`p)?&srn_U
ziMhH3Mfu68#l^b0i3OXNGrnOmm`0+m$&J#fn+;j7v682ADfbs{gQcX~S-sg;;x`k?
rIyW~;OK};jBGtZ)nhl#n)Kr*B*0~v|Q_!HFRQnpG6E>f+u3`iLxYe`Z

delta 541
zcmexUd8CT9fpw~-?MBv2M$0t)(BjmhV*QHLj8c7<)Z*-t`~v-u)WlqcfTH~5)Z$_V
z-^7A~%)E5{5};swa(-@Zd`W(OPVwe>jBl7M=aZ{_@;dR<&GM|*SSd4NvOFvM=84>I
zxh>a`>ypju#LJk;*ADbZ_2%=^^EoXylkI|es!N#3*FJfkYQy4Bnu3-y$aMhF4+)!_
Htg9FSEQZiF

diff --git a/docs/build/doctrees/features/fflow.doctree b/docs/build/doctrees/features/fflow.doctree
index 77d54954ea108170ad707d1bc99963a8569af2e5..45feb406223a485c30b0cfe0ee34225bb63f63a5 100644
GIT binary patch
delta 238
zcmZ4B@yDIDfpzLf<&CVKj0S%Cp~b01#rl<{6{U%JRT=s&`N^fZsd**E`p)?&srn_U
ziMhH3Mfu68#l^b0i3OY68Rsw=G?A(+hQ)}DWL=YESRyvdb1R4&6q0BkP^Z)8T}o+;
E0Fs4RU;qFB

delta 274
zcmez4zQBXEfpw~=%0^aCM$2&h(BjmhV*QHLj8c7<)Z*-t`~v-u)WlqcfTH~5)Z$_V
z-^7A~%)E5{5};swa(-@Zd`W(OPVweC#yL!u-Q;SYyoM`c^CFg8tmGT9c@0;ExMdXu
ME^yjBO(~5L0M@E!VE_OC

diff --git a/docs/build/doctrees/features/get_all_DD_features.doctree b/docs/build/doctrees/features/get_all_DD_features.doctree
index a15d9bfa394f7b83b30ade6c6db818ecfc742fbd..4ad378f95b20418aeea24988ff1c69e458792e65 100644
GIT binary patch
delta 360
zcmX?GI=z&ofpu!nMwT2#gBbnL;?$yI{mRmc(!{)~41JgUC75lMRqI=q1tK&HpXVF#-U%>x$?A

delta 415
zcmbPUdbX6MfpzMkjVw8gmZ|!o#i>Qb`W2}erTQ+Z#n~nK1^OYWiMa{^Mfu68#l;G~
zi3J6jdFlEkK*9Lr{M_95lKlLf;>`;fZ!uY}AXocjUe40Z@~r!q$v0v%&|&f7!^*@~k;*Wa*qN&nmjvh-ZqR!7LK(-TYrR
inT2FsK-U&*=2kWpHfSf&KA_Hs$@;9Uo3EK=GXemV28jCr

delta 411
zcmeA!I9R~az&h1zBTEXSWs-hqacWVqeno0VslH2Uadt_5fqqD8Vy;3!QGRl2aj}AL
zVnIP>Ub=n>P%u6@KQ}kNBtJi=c=HU#H%yib$<;nNPbqRUFKZ4PWkyWqWfk2l&ND^O
iaxn!iDcI~S_nDb|BR1zLEfuz$K!FP)HqSOIU<3fSa+_%2kMgu?n(BjmhV*Sd}iqgcqstkRX{N&Qy)Vz{nedqj?RQ;0F
z#9ZBiqWt94;$q$0#DdN3jD1W7ZKUe*V+mv-S=VGgmYB^ZoIivN3Q4pNsMBfla+x$n
E0C!4Q#{d8T

delta 278
zcmaE9-D|_zz&e#lZX>HFqh+{$XmM&$v3^BrMyb9_YH@Z+et~{SYGSTJKv8~jYH_iG
zZ(>0~W?s5}2~aRTIX^cyz9c_Cr+9N6V;_@cKe^f`JIXjs{?8$`c?Qc@X3C7&{GUTe
P*s_XTmuz;FS-}VZ+G}Uc

diff --git a/docs/build/doctrees/features/index.doctree b/docs/build/doctrees/features/index.doctree
index bd61a581a4e0fa324eaae2b13e0dfbb48839dbd9..84ca888f343cd73470b72a02e2eb46423c8568a5 100644
GIT binary patch
delta 67
zcmZ3QJ|~@}fpzM{jVzjs27daX#i>Qb`jw>>rHOe}8Tu~y$)&lec_qdA&iN^+`X#A}
Wxw-{K`N^rp#k#qP1)I|t?Tr9O!Wf$X

delta 76
zcmbP}zBHYsfpzMvjVzjsmf`xL#i>Qb`W2}erTQ+Z#n~nK1^OYWiMa{^Mfu68#l;G~
ei3J6jdFlEkK*9Lr{M_95lKlLf;?1#)_C^3K6&wBl

diff --git a/docs/build/doctrees/features/info_exchange_zscore.doctree b/docs/build/doctrees/features/info_exchange_zscore.doctree
index 31e4e4f94c7395313ca317430c07797c553415fa..9afa5dc7141f6ae78808bd40eb628c58622de573 100644
GIT binary patch
delta 238
zcmbOo^F5lifpzK|-Hoi-j0Um#p~b01#rl<{6{U%JRT=s&`N^fZsd**E`p)?&srn_U
ziMhH3Mfu68#l^b0i3OWiGD&TgcTu*-$58vL3VC<_y+)Rw@`Xl{-hl
Oat67s*=(qDj1d4%sc2RJ

diff --git a/docs/build/doctrees/features/information_diversity.doctree b/docs/build/doctrees/features/information_diversity.doctree
index 360850465b7dfddb0627112872c3eb8cec05e329..d2ad7f47a124fab8e0dc4794d1128686c643b009 100644
GIT binary patch
delta 608
zcmbPnh;iRRM%D(_shblvvSu?H#Oa3?rxq3KSC&?kCgxRT=)2@6m*%GCl@#kc=clCV
zm!u}<>J}8`C#Mz{>*gjFY+lLupUGeesk$DrEM+5E*W`yRRhun&)(DZKGkLOrs`z9d
zbKcEM<|S`5%8c3k-ft(rzJ(D0fp!IH

diff --git a/docs/build/doctrees/features/lexical_features_v2.doctree b/docs/build/doctrees/features/lexical_features_v2.doctree
index d05e2d67d5ea3a177ba3b8b25cb8ecb62dac62d9..2f4af013893c33487e6e688b0bdc99f62c02edaf 100644
GIT binary patch
delta 416
zcmeC`VLaW<$kM<%^}t4!EJlME{m|mnqGJ8Z(u&f=ys8X+m;B_?+|<01VtwcQlvMqa
z)Wlrff};H7)Z${@+{A*(%Ng$(^pdD)^FF3*W`j8->Y98`Gk)?J7JeMig3P>h{Su&Hd~$wnZhT38eopb^d5rfgr;)9DzGU2HE@ob4%cT?;5kGksi@@e>
rY&dpIEQ(4K9gLR6`k}?CMaB9RsTrmEE~&-YCHV#VA*qSE3IRp=$*IM~
z3ciU21(|v2`XxZY_~iWD-1w6G{G8&=dl=oAEf0~aeX@dg_2dR-!Oi6u6{jbArh&X3C71oM0lf`G>_M
zUdzK2xMad+FZX54vN<-YLeO#(1wm1@xjv_l5ddE!
BJGuY>

diff --git a/docs/build/doctrees/features/other_lexical_features.doctree b/docs/build/doctrees/features/other_lexical_features.doctree
index fcb6a4717534321d6adb651016245a2525e122c2..7ea2100596e9b786c33c52ca8f73b5758b4af6bf 100644
GIT binary patch
delta 483
zcmZ42!1%15wSjf&ZTpR^`HTkf`k}?CMaBA+r4^-#c~u$uF8Rr&xv6<2#rn?qDXID;
zsfoF|1x5MEsl~;*xrqgv*D^k3GFV8WuE_y*DVz0KKQWV~bFx0G@aBu0{JaJm$+5Rq
zdzpjCiwSjf2vcpE!d`8O*{m|mnqGJ7u)QnPnm(=3ylKcYwkkrIng@B^`eMig3P>h{Su&Hd~$wnZhT38eopb`C5%s*ELV}MeX^r;>STRp{>{3qkC>@o%w|p@
zUdvq+xTbw`jrde%@{QQ+C|%2Ixsn1GWKO=X!@D^}^AQte#%#W?^Hacb4h1er*_>ln
G#RveirqPf9

diff --git a/docs/build/doctrees/features/politeness_features.doctree b/docs/build/doctrees/features/politeness_features.doctree
index 6b3321be25043107b04b786be119e6190cb36fe5..0d9aca9f05c85715de572bcdf84faf61e00ac9cc 100644
GIT binary patch
delta 237
zcmX?Rx5$pAfpx0*MwSdlgBbnL;?$yI{mRmc(!{)~41JgU|w+9w}isomVcwM@uz8o4e2
M8WFd7k8Bzv0RE0>1poj5

diff --git a/docs/build/doctrees/features/politeness_v2.doctree b/docs/build/doctrees/features/politeness_v2.doctree
index 7188916174818fe95bd2cbe4a00a05dcfa55d012..5d789f45b040969edb089f7eaed858d7bc1b4255 100644
GIT binary patch
delta 238
zcmeBodF{;Fz&iDT;zrhJMuRZ@(BjmhV*Sd}iqgcqstkRX{N&Qy)Vz{nedqj?RQ;0F
z#9ZBiqWt94;$q$0#DdK;8Fw=oOeR%VFUwXol66h)Wy#$9gxgBQppiuTfI5RVuT)55
F1OP+%TA%;`

delta 274
zcmaFu-0#BLz&e#hX(MYiqh-8)XmM&$v3^BrMyb9_YH@Z+et~{SYGSTJKv8~jYH_iG
zZ(>0~W?s5}2~aRTIX^cyz9c_Cr+D)O#@$SobI8>`Ie|NK^Ai>yHu8?~rpa&5VdI&{O1XIC-;=#1G=t1Iasy#b1_iz3;@Bin`d|8s8
zEXejDISteH9zY%bBXJ`Z_a_tQ6MFB!X@5&!S0ZBc_Q(DE`c4}DenXEmL}PtjMm*jS
z(WB%cyt1L&oD|l5I#K1EBt&9W)<{ShQqh=*?m+chNsRpJxu~JL{F*T{>;)&OtFMx{
zaiaV7s%V5)bhs&+ZQUVpgJihrseRC-&^$|uOgyj|ezjKmZ3F4DeqP+)e>l_TbN3GC@(@ZOOgPp+!0GX)R6
z*|ME>1AGMjYsWUFY|}c0`vqWqI7M?B`1l_W3pE+4(#z|hTR{(aqt6;?e%Ju(>DWg2
zX~Vfij$yvS9@q>Ch2MU5?aV`Mu$p#wVVgh*{_!T`Rl2hQUMoVsjO8NkHChIU{BJ6}
z$#@4nw;N^!0{QnOF1olMUfB4v$9T#*X^2VF;9*!0Q#BdtqTh~!DG+<>)R&I4u6cF1
ZFOdBe{;UC;+$hDHecczL^+{;9{Q**kc9Z}B

delta 3389
zcmb`J&ubGw6vv&NtZ_oNNvuK)RVqR(70f{^&ZUPKs31ZM_FzTR7?N7eFSC(WgH)(^
z2_DK=PXh`K5^iiTu^nT6?c^~V*CN9ZyxCIzDnKaQXNX??XosaJMfMFQEXuqw{
zIfxQob{@ts1S>mj{6Y6;LT5orYR4@Yh?qKgp3r9?6-oC?8HQjJgtp?!Sm;v}KZAxc<&d?)J-6238##Vta0hh`P}3aDx?S8pLh3owp}dkV1WGbx4l
z-v5qUfLWL-n?Yrc@B@!cuuetz^3xgtmG&kd&K<=15xkJ^G0_(wk7Oz`D;6z0^?nA!
zQM_2}htAtfWd%BKGZh;*ueK>5kN8-ovWxTew=kdl#~3z^kh)asah|KyCH;GdSL;iV
z$zN)O$@K2zj;)6s{kw**uG*RH!m))jXdMAEU20qxWeIgamSd?AO#d_?qqu8Ehaf9*
z8|1N~2%+=3qgAb679Iy`!$8L7ev~5myWTwP-gKcJV4xm$A)EMi1brf~b1WTmB9i_?
zk%{GMiWoS7Y`_C=izqbW8pPaMm6{-IqCfpx0yMwTc>gHZj@;?$yI{mRmc(!{)~41JgUOV

delta 269
zcmccN^2ddxfpu!(MwTc>%Q*ee;?$yI{fg9#Qhk@y;_QW3Dm78UDPq-K=ryQCIpm*f}dhomOvDg+eeC#Mz{
zEBGcB6lCV5>z4opJ}8`C#Mz{>*gjFY@W(Eo5`SuL|v07I)qOCz{Iur1WN@o`MPg#+~+iyNRHjS
z;zFClg*BMT(!H5i+>VnRSBFhbkmsBnA}lbu)|zAUZ-pOZg&f$F&D|>UoCaN_`#pT}
zIz!IM;ljL|1N6=@k!8Z>b%yF>`9EoMf%OX(l0$CuM2ESY2K}V_HFUC{pTOobUSF8V
z(!JTwPoLAElN@{Fqq)FgtQ4`Hi7XQ~$46^&8uXHA_vV8swag^zntU)NdGoCdbMnG?
z^ZcSDX7a+fzs!lOG#t7)zCnbUoU|J{Ilh5=Gfzt(r@>4T!xmI#ZGPQ5hnXy$lVA5r
rZPuRzw0AN&_VUefVxBB#$e}@OxeRvgz4;IL3~EWY&u_Eq`YVh88Xs8(

delta 1786
zcmZ4gfNACbs;CXP4v`=!c{x<|+gf=+Rb93WM^7C_wH}^2kX0n`0uJ*}>DWRL!urx7KX2j$*EWDc!
zaNOavoJEOCCO;4pnmj$6ce8`AG&5yJZGIqT$4Qx|HZN9?qA*-GJE>@LT27`UOg4Ye
zea1wY5tBdYa&JyEl%q5}IIX|3P!^<ypieDYeYxYX=qr$(tQB%qfkPzlBMZ#>(G9
zfz4k^jVR1BlkMs_CQk_$*nGJD52bkrXw+t(<`7QHMdZfLvJ+Z?^_3L^liz^qmP

diff --git a/docs/build/doctrees/features/temporal_features.doctree b/docs/build/doctrees/features/temporal_features.doctree
index d2688009b313078072f20463be33cb7da204a4e6..4cd8913815ca3ff3a29ab773fc1d9cda1402e87a 100644
GIT binary patch
delta 491
zcmZ3ymhtu)MwSNFsR0{VQWy=Q^h1kNi;DFtODjqf^QtoRUGkGlb5rw5iuIlIQ&ROy
zQWJA^3ySiSQ;Umra}x_TFJyeeWUz=tU6ap;L`{}umfmd4x`u^(-Mw78>;}`xv0Ffo
wZ*#Oz7aRGy+a$jW8!RBh?#%*vx7o?kIaxqYX7enwKe7g$B-*?Ae8?3>0PnrLH~;_u

delta 551
zcmcb;hH>#)MwSNFsWUdRq%c}0>xUMn78UDPq-K=ryQCIpm*f}dhomOvDg+eeC#Mz{
zEBGcB6lCV5>z4opU-{
zxwBg?pui=$n{9+z*~m9y^GAtz5zCbnxFBP)uNmLwZ@T;0DKloXuNjw|lBTE&dL5hB8acWVqer0JzX<}YghQ3RFa%paAUP-aObAC#yeo1O#
zu5Lk5esXGYv2Jc+!RGCZlFSAhNYpjCm$PkiKkHG_b#CtEloK%6Lb`p$ll|qyH|I&2
YGLxlyv%g%Fh{0Ua?akX9U|hfm0FXF_)c^nh

delta 415
zcmeCmJdnxKz&ds7MwTi@%Uu1?;?$yI{fg9#Qhk@y;_QhIcE{eW#qa5Xhhy-DdPf00C8cSnE(I)

diff --git a/docs/build/doctrees/features/turn_taking_features.doctree b/docs/build/doctrees/features/turn_taking_features.doctree
index 9e6183a2189dc58b60972ab1c17d9ac33ed8747b..2756ea9d4b0f45c7bc08fdf7f4795f821ab254b7 100644
GIT binary patch
delta 488
zcmZ26h4H~;M%D(_saHKWvSu?H#Oj9@rxq3KSC&?kCgxRT=)2@6m*%GCl@#kc=clCV
zm!u}<>J}8`C#Mz{>*gjFY+lL8&1|roL|u~~Y9~&v=aSi+#ahimmhR2DPmY&l+k9E}DzCu|67ApoP+O3dWL?0}%G*5CutvQb`jw>>rHOe}8Tu~y$)&lec_qdA&iN^+`X#A}
uxw-{K`N^rp#k#qP1)JwGK4UVNMxw6Cj6xxs1z30R7&Mcpb2FpRE=B-&^+JyT

delta 206
zcmZ3WzFVE8fpzMJjVuX_mI?Zy#i>Qb`W2}erTQ+Z#n~nK1^OYWiMa{^Mfu68#l;G~
zi3J6jdFlEkK*9Lr{M_95lKlLf;>}YSpD|g^CtLd}79L*99&)u$Ud0l!*-9vl5da}I
BO*jAm

diff --git a/docs/build/doctrees/features/within_person_discursive_range.doctree b/docs/build/doctrees/features/within_person_discursive_range.doctree
index ccbfcb966be4d70f8d7847cd3003f035183589b6..3c4f87fe54205b9678522eb561285b161ae1cda4 100644
GIT binary patch
delta 237
zcmaECvfqTIfpx0MMwTWfpu!cMwTW<%L4t-;?$yI{fg9#Qhk@y;_QPfjf^*3C^U*gT!_A(O#WQgv-)VP+>;*W`^X*_$JHI0X&nk!T-KXWAyY
zJ`S=pPLku>Y^{Ea-=LFpTLUKx__J?bX8xL)eBDYm9DD{7$+KH*^C_=A%w*}_Ea30S
zYcPvEdj%)|i{jk;H|7pAWhT@n8uJ=VBgYMMawRqg<*#NYU-$gt*<1#5$gz9D4wlI|
z&9am8Ch~6nRQHCNY*RMpG>7pT%q7zen*%1Au#l~La==8n%?8tCcnv0yXFu!a+l$|`
zkga?2?ZpC{GgpQP7)&D1ev!@5yEd_quY2`=V*!J1a_sK9DzLfYLI(?3x;J-Sy&-B)
OPrAJUn_s^^#Rvd}XhrY<

delta 1708
zcmcb6lX>fHX4VGQsjJ>@WQ}CBjMEP-PAw|duSm@()ptoP&MwI>&<{yX%vA^|%1=%$
zE>`eOEGWp#OV=*}3dSer=jO(jT$GW-6YY+3}`UDO`l9LN4z9%ILZoc4W!E3pgGPlT2ekIGhd27rmX39+3
zl<3QAIiCWz$9sK|R

diff --git a/docs/build/doctrees/features_conceptual/function_word_accommodation.doctree b/docs/build/doctrees/features_conceptual/function_word_accommodation.doctree
index cd5efa41a9eebed62c35936c7c4bf2663350c917..59ba1aede81151bcd22d24bd9b1273575710e298 100644
GIT binary patch
delta 69
zcmew{oALc@MwSNFsZTbtSTh>r>xUMn78UDPmR6J|=2d0ryW}UA=BDPA6zez4opQb`jw>>rHOe}8Tu~y$)&lec_qdA&iN^+`X#A}
Wxw-{K`N^rp#k#qP1)DP%t0e$lxfvb+

delta 76
zcmca*{MeYKfpzMQjV#)XmPz`d#i>Qb`W2}erTQ+Z#n~nK1^OYWiMa{^Mfu68#l;G~
ei3J6jdFlEkK*9Lr{M_95lKlLf;?41l)e-y;?$yI{fg9#Qhk@y;_Qvn

diff --git a/docs/build/doctrees/features_conceptual/moving_mimicry.doctree b/docs/build/doctrees/features_conceptual/moving_mimicry.doctree
index 6025aa389570e343fee64d5d1e37bffa8facea20..2bcd650e8cd00c82a3471b449cf8842e67717dea 100644
GIT binary patch
delta 67
zcmdmzvpR>Rfpx0FMixazgCzaX;?$yI{mRmc(!{)~41JgUk)?rk>XD5sri=zT`k}?CMaBA+r4^-#c~u$uF8Rr&xv6<2#rn?qDXID;
YsfoF|1x5MEsl~;*xrqgvix|^f0FELV?EnA(

delta 78
zcmX@#&3L1mk)?rk>e-Dfri_-Q`k}?CMaB9RsTrmEE~&-YCHV#VA*qSE3IRp=$*IM~
g3ciU21(|v2`XxZY_~iWD-1w6G{G8&=nT%;J0DIvbPyhe`

diff --git a/docs/build/doctrees/features_conceptual/positivity_bert.doctree b/docs/build/doctrees/features_conceptual/positivity_bert.doctree
index fd57f3d28c4949fc45836c40ee9800827e1029f8..2a20c9f5f8361b4788e84c9e3946f5f2c2126f36 100644
GIT binary patch
delta 67
zcmeCk{h!0qz&f>LBa1SlL9%{macWVqer0JzX<}YghQ3RFa%paAUP-aObAC#yeo1O#
Wu5Lk5esXGYv2Jc+!R7=;4O0MEF&M-E

delta 76
zcmeyL(~-;4z&f>dBa1SlWsZJmacWVqeno0VslH2Uadt_5fqqD8Vy;3!QGRl2aj}AL
eVnIP>Ub=n>P%u6@KQ}kNBtJi=cylUb=n>P%u6@KQ}kNBtJi=cyl!4W?KLea2yl>

diff --git a/docs/build/doctrees/features_conceptual/word_ttr.doctree b/docs/build/doctrees/features_conceptual/word_ttr.doctree
index a9f3baff295a82d92bbd9c6affda57083533684a..3d956590db4e7fec2b7c4e3e2bedca3ec0a2370f 100644
GIT binary patch
delta 67
zcmaFjblZugfpu!YMix;l>H=

diff --git a/docs/build/doctrees/index.doctree b/docs/build/doctrees/index.doctree
index 8b24805d076e034ec597e15e1cc58ba46c2e73d9..f02db4322b3a4638feceadcad611c90e7f80c77c 100644
GIT binary patch
delta 69
zcmZ4gf^pdkMwSNFsnQ!+BpD4{^+StOi;DFtODjqf^QtoRUGkGlb5rw5iuIlIQ&ROy
ZQWJA^3ySiSQ;Umra}x_ThcVtP0swSU8SVf8

delta 78
zcmZ4Xf^q!|MwSNFsVW;;BpEIJ^h1kNi;DFtQZq{RT~dp)OY#f!LsAoS6#|O#lT(X}
h6?_v53NrK3^-F+)@yYqQx$!0W`8ma#eHm{S0RUZX9Z>)P

diff --git a/docs/build/doctrees/intro.doctree b/docs/build/doctrees/intro.doctree
index 8d87292879612a221438aba1acde1717160062ab..7417cb6fa22300fc9539b8d038b6cac9241573aa 100644
GIT binary patch
delta 69
zcmaFV!*sKUiKT&cs^3NyentaV{m|mnqGJ8Z(u&f=ys8X+m;B_?+|<01VtwcQlvMqa
Y)Wlrff};H7)Z${@+{A*-K8#|m0B7VG4FCWD

delta 78
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diff --git a/docs/build/doctrees/utils/assign_chunk_nums.doctree b/docs/build/doctrees/utils/assign_chunk_nums.doctree
index 6fc95f688883d4910e0438fc24d8f20717d65cc8..330a34de723aaff83d263feeff3ba2d60689f7ac 100644
GIT binary patch
delta 627
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delta 705
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diff --git a/docs/build/doctrees/utils/calculate_chat_level_features.doctree b/docs/build/doctrees/utils/calculate_chat_level_features.doctree
index 4bd1d9abe5536f6acba3fcda489503eb15daa015..c1f12f2441d5045ef222cad4053d7c41415ff0ba 100644
GIT binary patch
delta 2705
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diff --git a/docs/build/doctrees/utils/index.doctree b/docs/build/doctrees/utils/index.doctree
index b0545b833e6bad0c2fb41555fbf9a68f9f76ce09..69ac1835b8847a7777228da6787e354d7280274a 100644
GIT binary patch
delta 67
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delta 76
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index 8953185647124dd49a4e3b4b96cbdb9d6524206a..7a72158ae20e31a01b86b1fc8e4e788309970c45 100644
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delta 587
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diff --git a/docs/build/doctrees/utils/preprocess.doctree b/docs/build/doctrees/utils/preprocess.doctree
index 7b868cc7a374155a64e7a71ce2c2946b874a06be..1ffc189d92ebd2e1cbd8658ec963b67247223cff 100644
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delta 1076
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zpgal^J20swO#k4=CWorked Example
 
                • Features: Technical Documentation
                  • 
 
                • Features: Conceptual Documentation
                  • 
-
                • feature_builder module
-
                  • 
+
                • feature_builder module
                  • 
 
                • Utilities
                  • 
 
                
 
@@ -93,246 +79,8 @@
           
                
            
                
              
-  
                
-
                feature_builder module
                
-
                
-
                
-class feature_builder.FeatureBuilder(input_df: DataFrame, vector_directory: str = './vector_data/', output_file_base: str = 'output', output_file_path_chat_level: str = None, output_file_path_user_level: str = None, output_file_path_conv_level: str = None, custom_features: list = [], analyze_first_pct: list = [1.0], turns: bool = False, conversation_id_col: str = 'conversation_num', speaker_id_col: str = 'speaker_nickname', message_col: str = 'message', timestamp_col: str | tuple[str, str] = 'timestamp', timestamp_unit='ms', grouping_keys: list = [], cumulative_grouping=False, within_task=False, ner_training_df: DataFrame = None, ner_cutoff: int = 0.9, regenerate_vectors: bool = False, compute_vectors_from_preprocessed: bool = False, custom_liwc_dictionary_path: str = '', convo_aggregation=True, convo_methods: list = ['mean', 'max', 'min', 'stdev'], convo_columns: list = None, user_aggregation=True, user_methods: list = ['mean', 'max', 'min', 'stdev'], user_columns: list = None)
                
-
                Bases: object
                
-
                The FeatureBuilder is the main engine that reads in the user’s inputs and specifications and generates
-conversational features. The FeatureBuilder separately calls the classes
-(ChatLevelFeaturesCalculator, ConversationLevelFeaturesCalculator, and
-UserLevelFeaturesCalculator) to generate conversational features at different levels.
                
-
                
-
                Parameters:
                
-
                  
-
                • input_df (pd.DataFrame) – A pandas DataFrame containing the conversation data that you wish to featurize.
                  • 
-
                • vector_directory (str) – Directory path where the vectors are to be cached. Defaults to “./vector_data/”.
                  • 
-
                • output_file_base (str) – Base name for the output files, used to auto-generate filenames for each
-of the three levels. Defaults to “output.”
                  • 
-
                • output_file_path_chat_level (str) – Path where the chat (utterance)-level output csv file is
-to be generated. This parameter will override the base name.
                  • 
-
                • output_file_path_user_level (str) – Path where the user (speaker)-level output csv file is
-to be generated. This parameter will override the base name.
                  • 
-
                • output_file_path_conv_level (str) – Path where the conversation-level output csv file is to be
-generated. This parameter will override the base name.
                  • 
-
                • custom_features (list, optional) – A list of additional features outside of the default features that should
-be calculated. Defaults to an empty list (i.e., no additional features beyond the defaults will
-be computed).
                  • 
-
                • analyze_first_pct (list(float), optional) – Analyze the first X% of the data. This parameter is useful because the
-earlier stages of the conversation may be more predictive than the later stages. Defaults to [1.0].
                  • 
-
                • turns (bool, optional) – If true, collapses multiple “chats”/messages by the same speaker in a row into a
-single “turn.” Defaults to False.
                  • 
-
                • conversation_id_col (str, optional) – A string representing the column name that should be selected as
-the conversation ID. Defaults to “conversation_num”.
                  • 
-
                • speaker_id_col (str, optional) – A string representing the column name that should be selected as the speaker ID.
-Defaults to “speaker_nickname”.
                  • 
-
                • message_col (str, optional) – A string representing the column name that should be selected as the message.
-Defaults to “message”.
                  • 
-
                • timestamp_col (str, optional) – A string representing the column name that should be selected as the message.
-Defaults to “timestamp”.
                  • 
-
                • timestamp_unit (str, optional) – A string representing the unit of the timestamp (if the timestamp is numeric).
-Defaults to ‘ms’ (milliseconds). Other options (D, s, ms, us, ns) can be found on the Pandas
-reference: https://pandas.pydata.org/docs/reference/api/pandas.to_datetime.html
                  • 
-
                • grouping_keys (list, optional) – A list of multiple identifiers that collectively identify a conversation. If
-non-empty, the data will be grouped by all keys in the list and use the grouped key as the unique
-“conversational identifier.”
                  • 
-
                • cumulative_grouping (bool, optional) – If true, uses a cumulative way of grouping chats (looking not just within
-a single ID, but also at what happened before). NOTE: This parameter and the following one
-(within_grouping) were created in the context of a multi-stage Empirica game (see:
-https://github.com/Watts-Lab/multi-task-empirica). Assumes exactly 3 nested columns at different
-levels: a High, Mid, and Low level; that are temporally nested. Defaults to False.
                  • 
-
                • within_task (bool, optional) – If true, groups cumulatively such that only prior chats of the same “task”
-(Mid-level identifier) are considered. Defaults to False.
                  • 
-
                • ner_training_df (pd.DataFrame, optional) – A pandas DataFrame of training data for named entity recognition features.
-Defaults to None and will not generate named entity features if it does not exist.
                  • 
-
                • ner_cutoff (int) – The cutoff value for the confidence of prediction for each named entity.
-Defaults to 0.9.
                  • 
-
                • regenerate_vectors (bool, optional) – If true, regenerates vector data even if it already exists. Defaults to False.
                  • 
-
                • compute_vectors_from_preprocessed (bool, optional) – If true, computes vectors using preprocessed text (with
-capitalization and punctuation removed). Defaults to False.
                  • 
-
                • custom_liwc_dictionary_path (str, optional) – This is the path of the user’s own LIWC dictionary file (.dic). Defaults to empty string.
                  • 
-
                • convo_aggregation (bool, optional) – If true, aggregates features at the conversational level. Defaults to True.
                  • 
-
                • convo_methods (list, optional) – Specifies which aggregation functions (e.g., mean, stdev) to use at the
-conversational level. Defaults to [‘mean’, ‘max’, ‘min’, ‘stdev’].
                  • 
-
                • convo_columns (list, optional) – Specifies which columns (at the utterance/chat level) to aggregate for the
-conversational level. Defaults to all numeric columns.
                  • 
-
                • user_aggregation (bool, optional) – If true, aggregates features at the speaker/user level. Defaults to True.
                  • 
-
                • user_methods (list, optional) – Specifies which functions to aggregate with (e.g., mean, stdev) at the user level.
-Defaults to [‘mean’, ‘max’, ‘min’, ‘stdev’].
                  • 
-
                • user_columns (list, optional) – Specifies which columns (at the utterance/chat level) to aggregate for the
-speaker/user level. Defaults to all numeric columns.
                  • 
-
                
-
                
-
                Returns:
                
-
                The FeatureBuilder writes the generated features to files in the specified paths. The progress
-will be printed in the terminal, indicating completion with “All Done!”.
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
                
-chat_level_features() → None
                
-
                Instantiate and use the ChatLevelFeaturesCalculator to create chat-level features.
                
-
                This function creates chat-level features using the ChatLevelFeaturesCalculator
-and adds them to the self.chat_data dataframe. It also removes special
-characters from the column names.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-conv_level_features() → None
                
-
                Instantiate and use the ConversationLevelFeaturesCalculator to create conversation-level features.
                
-
                This function creates conversation-level features using
-the ConversationLevelFeaturesCalculator, and adds them to the self.conv_data dataframe.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-featurize() → None
                
-
                Main driver function for feature generation.
                
-
                This function creates chat-level features, generates features for different
-truncation percentages of the data if specified, and produces user-level and
-conversation-level features. Finally, the features are saved into the
-designated output files.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-get_first_pct_of_chat(percentage) → None
                
-
                Truncate each conversation to the first X% of rows.
                
-
                This function groups the chat data by conversation_num and retains only
-the first X% of rows for each conversation.
                
-
                
-
                Parameters:
                
-
                percentage (float) – Percentage of rows to retain in each conversation
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-merge_conv_data_with_original() → None
                
-
                Merge conversation-level data with the original dataset, so that we retain all desired columns, both original and generated.
                
-
                If the conversational identifier was generated by our system (as opposed to an existing column in the original dataset),
-the function uses the preprocessed data, which contains the generated ID. Otherwise, it uses the original dataset.
                
-
                The function groups the original conversation data by “conversation_num” and merges it with the
-conversation-level data (conv_data). It drops duplicate rows and removes the ‘index’ column if present.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-preprocess_chat_data() → None
                
-
                Call all preprocessing modules needed to clean the chat text.
                
-
                This function groups the chat data as specified, verifies column presence, creates original and lowercased columns, preprocesses text, and optionally processes chat turns.
                
-
                
-
                Parameters:
                
-
                  
-
                • turns (bool, optional) – Whether to preprocess naive turns, defaults to False
                  • 
-
                • col – Columns to preprocess, including conversation_id, speaker_id and message, defaults to None
                  • 
-
                • within_task (bool, optional) – Whether to group within tasks, defaults to False
                  • 
-
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-save_features() → None
                
-
                Save the feature dataframes to their respective output file paths.
                
-
                This function saves the chat_data, user_data, and conv_data dataframes
-to the respective CSV files specified in the output file paths provided during initialization.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-set_self_conv_data() → None
                
-
                Derives the base conversation level dataframe.
                
-
                Set Conversation Data around conversation_num once preprocessing completes.
-We need to select the first TWO columns, as column 1 is the ‘index’ and column 2 is ‘conversation_num’.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
                
-user_level_features() → None
                
-
                Instantiate and use the UserLevelFeaturesCalculator to create user-level features.
                
-
                This function creates user-level features using
-the UserLevelFeaturesCalculator, and adds them to the self.user_data dataframe.
-It also removes special characters from the column names.
                
-
                
-
                Returns:
                
-
                None
                
-
                
-
                Return type:
                
-
                None
                
-
                
-
                
-
                
-
-
                
-
+  
                
+
                feature_builder module
                
 
                
 
 
diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html
index 9cbdd0d1..d8ad099a 100644
--- a/docs/build/html/genindex.html
+++ b/docs/build/html/genindex.html
@@ -131,14 +131,10 @@ 
                C
                
 
-  
+  
                
   
                  
       
                • conv_to_float_arr() (in module features.get_all_DD_features)
-
                  • 
-      
                • ConversationLevelFeaturesCalculator (class in utils.calculate_conversation_level_features)
 
                  • 
       
                • count_all_caps() (in module features.reddit_tags)
 
                  • 
@@ -261,15 +247,6 @@ 
                  F
                  
 
-  
+  
                  
   
-  
                    
       
                  • 
     features.other_lexical_features
 
@@ -364,6 +339,8 @@ 
                    F
                    
         
                  • module
 
                    • 
       
                  
+  
                    
       
                  • 
     features.politeness_features
 
@@ -448,8 +425,6 @@ 
                    F
                    
         
                  • module
 
                    • 
       
                  
-      
                • featurize() (feature_builder.FeatureBuilder method)
-
                  • 
       
                • fix_abbreviations() (in module utils.check_embeddings)
 
                  • 
       
                • function_mimicry_score() (in module features.word_mimicry)
@@ -467,16 +442,12 @@ 
                  G
                  
       
                • generate_lexicon_pkl() (in module utils.check_embeddings)
 
                  • 
       
                • generate_vect() (in module utils.check_embeddings)
-
                  • 
-      
                • get_centroids() (utils.calculate_user_level_features.UserLevelFeaturesCalculator method)
 
                  • 
       
                • get_certainty() (in module features.certainty)
 
                  • 
       
                • get_certainty_score() (utils.calculate_chat_level_features.ChatLevelFeaturesCalculator method)
 
                  • 
       
                • get_content_words_in_message() (in module features.word_mimicry)
-
                  • 
-      
                • get_conversation_level_aggregates() (utils.calculate_conversation_level_features.ConversationLevelFeaturesCalculator method)
 
                  • 
       
                • get_cosine_similarity() (in module features.discursive_diversity)
 
                  • 
@@ -491,10 +462,6 @@ 
                  G
                  
       
                • get_dep_pairs() (in module features.politeness_v2_helper)
 
                  • 
       
                • get_dep_pairs_noneg() (in module features.politeness_v2_helper)
-
                  • 
-      
                • get_discursive_diversity_features() (utils.calculate_conversation_level_features.ConversationLevelFeaturesCalculator method)
-
                  • 
-      
                • get_first_pct_of_chat() (feature_builder.FeatureBuilder method)
 
                  • 
       
                • get_first_person_words() (in module utils.preload_word_lists)
 
                  • 
@@ -509,8 +476,6 @@ 
                  G
                  
       
                • get_function_words_in_message() (in module features.word_mimicry)
 
                  • 
       
                • get_gini() (in module utils.gini_coefficient)
-
                  • 
-      
                • get_gini_features() (utils.calculate_conversation_level_features.ConversationLevelFeaturesCalculator method)
 
                  • 
       
                • get_info_diversity() (in module features.information_diversity)
 
                  • 
@@ -571,16 +536,8 @@ 
                  G
                  
       
                • get_turn() (in module features.turn_taking_features)
 
                  • 
       
                • get_turn_id() (in module utils.preprocess)
-
                  • 
-      
                • get_turn_taking_features() (utils.calculate_conversation_level_features.ConversationLevelFeaturesCalculator method)
 
                  • 
       
                • get_unique_pairwise_combos() (in module features.discursive_diversity)
-
                  • 
-      
                • get_user_level_aggregates() (utils.calculate_conversation_level_features.ConversationLevelFeaturesCalculator method)
-
                  • 
-      
                • get_user_level_summary_statistics_features() (utils.calculate_user_level_features.UserLevelFeaturesCalculator method)
-
                  • 
-      
                • get_user_level_summed_features() (utils.calculate_user_level_features.UserLevelFeaturesCalculator method)
 
                  • 
       
                • get_user_max_dataframe() (in module utils.summarize_features)
 
                  • 
@@ -591,11 +548,7 @@ 
                  G
                  
       
                • get_user_min_dataframe() (in module utils.summarize_features)
 
                  • 
       
                • get_user_network() (in module features.get_user_network)
-
-      
                  • 
       
                • get_user_stdev_dataframe() (in module utils.summarize_features)
 
                  • 
       
                • get_user_sum_dataframe() (in module utils.summarize_features)
@@ -654,16 +607,12 @@ 
                  L
                  
 
                  M
                  
 
                  
   
   
                    
-      
                  • preprocess_conversation_columns() (in module utils.preprocess)
-
                    • 
       
                  • preprocess_naive_turns() (in module utils.preprocess)
 
                    • 
       
                  • preprocess_text() (in module utils.preprocess)
@@ -813,8 +756,6 @@ 
                    R
                    
 
                    S
                    
 
                    
   
                      
       
                    • sentenciser() (in module features.politeness_v2_helper)
 
                      • 
-      
                    • set_self_conv_data() (feature_builder.FeatureBuilder method)
+      
                    • sort_words() (in module utils.check_embeddings)
 
                      • 
       
                    • str_to_vec() (in module utils.check_embeddings)
 
                      • 
@@ -847,10 +788,6 @@ 
                      T
                      
 
                      U
                      
 
-  
+  
-     
-       
-       
@@ -245,16 +240,6 @@ 
                      Python Module Index
                      
-     
-       
-       
-     
-       
-       
                      
   
-  
                        
       
                      • 
     utils.gini_coefficient
 
@@ -895,6 +816,8 @@ 
                        U
                        
         
                      • module
 
                        • 
       
                      
+  
                        
       
                      • 
     utils.preload_word_lists
 
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index de04f500..9996e484 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -230,10 +230,7 @@ 
                        Table of ContentsConversation-Level Features
                        • 
 
                      
 
-
                    • feature_builder module
-
                      • 
+
                    • feature_builder module
                      • 
 
                    • Utilities
                        
 
                      • “Driver” Classes: Utterance-, Conversation-, and Speaker-Level Features
                        • 
 
                      • Other Utilities
                        • 
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diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html
index fc63afc0..e3e275ff 100644
--- a/docs/build/html/py-modindex.html
+++ b/docs/build/html/py-modindex.html
@@ -90,11 +90,6 @@ 
                        Python Module Index
                        
      
                      •  
                      
      
                      
        f
                      
-       feature_builder
-       
                      
      
                      
        
           
        utils.calculate_chat_level_features
        
                         
-       utils.calculate_conversation_level_features
-       
                         
-       utils.calculate_user_level_features
-       
                      
      
                      
        
           
diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js
index b06ea04c..e8662a7a 100644
--- a/docs/build/html/searchindex.js
+++ b/docs/build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"A Light-Touch, One-Function Package": [[0, "a-light-touch-one-function-package"]], "Additional FeatureBuilder Considerations": [[1, "additional-featurebuilder-considerations"]], "Advanced Configuration Columns": [[1, "advanced-configuration-columns"]], "Aggregation Overview": [[1, "id2"]], "Analyzing First Percentage (%)": [[1, "analyzing-first-percentage"]], "Base Conversation-Level Features": [[11, "base-conversation-level-features"]], "Basic Input Columns": [[1, "basic-input-columns"]], "Certainty": [[30, null]], "Citation": [[29, "citation"], [30, "citation"], [31, "citation"], [32, "citation"], [33, "citation"], [34, "citation"], [35, "citation"], [36, "citation"], [37, "citation"], [38, "citation"], [40, "citation"], [41, "citation"], [42, "citation"], [43, "citation"], [44, "citation"], [45, "citation"], [46, "citation"], [47, "citation"], [48, "citation"], [49, "citation"], [50, "citation"], [51, "citation"], [52, "citation"], [53, "citation"], 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"why": [20, 29, 31, 36, 54], "wide": 31, "wien": 62, "wiki": [21, 29, 70], "wiki_link": [1, 61], "wikipedia": [21, 33, 37, 70], "williamson": 60, "wish": [1, 18, 28], "within": [0, 1, 8, 11, 16, 28, 30, 31, 34, 35, 36, 41, 45, 46, 52, 55, 59, 60, 62, 63, 64, 68, 71, 73], "within_person_discursive_rang": 11, "within_task": [0, 1, 71], "without": [1, 19, 31, 36, 42, 47, 54, 62, 69], "won": [0, 31, 36, 45], "wonder": 56, "woolei": 4, "woollei": [13, 40, 55], "wooten": 55, "word": [0, 1, 3, 10, 11, 12, 13, 14, 16, 19, 20, 21, 22, 28, 30, 32, 33, 37, 38, 39, 40, 41, 43, 45, 46, 48, 49, 52, 53, 54, 56, 57, 62, 64, 67, 69, 70], "word_mimicri": 11, "word_start": [19, 49], "wordcount": [1, 42], "wordnet": [1, 61], "words_in_lin": 19, "work": [0, 11, 42, 47, 50, 55, 61, 62], "world": 55, "worri": 62, "would": [1, 29, 31, 34, 35, 36, 37, 42, 50, 54, 62], "wouldn": [31, 36], "wow": 50, "wp": 13, "wrap": 42, "write": [29, 60], "www": [12, 13, 18, 41, 64], "x": [0, 1, 4, 46, 68], "xinlan": 62, "yashveer": 62, "ye": 19, "yeah": [31, 36], "yeoman": [18, 49, 50], "yesno_quest": [32, 49, 54], "yet": 48, "ylatau": 12, "you": [0, 1, 11, 24, 29, 31, 36, 37, 42, 43, 47, 50, 59, 61, 62, 69], "your": [0, 29, 31, 32, 36, 37, 50, 59, 61, 62], "your_data": 42, "yourself": [31, 36, 50], "yuluan": 62, "yup": [31, 36], "yuxuan": 62, "z": [12, 39, 49, 51, 64, 73], "z0": 67, "za": 67, "zero": [13, 52], "zhang": 62, "zheng": 62, "zhong": 62, "zhou": 62, "zscore": 41, "zscore_chat": 41, "zscore_chats_and_convers": 69, "zscore_convers": 41, "\u00bc": 47, "\u03c4": 55}, "titles": ["The Basics (Get Started Here!)", "Worked Example", "feature_builder module", "basic_features module", "burstiness module", "certainty module", "discursive_diversity module", "fflow module", "get_all_DD_features module", "get_user_network module", "hedge module", "Features: Technical Documentation", "info_exchange_zscore module", "information_diversity module", "lexical_features_v2 module", "named_entity_recognition_features module", "other_lexical_features module", "politeness_features module", "politeness_v2 module", "politeness_v2_helper module", "question_num module", "readability module", "reddit_tags module", "temporal_features module", "textblob_sentiment_analysis module", "turn_taking_features module", "variance_in_DD module", "within_person_discursive_range module", "word_mimicry module", "FEATURE NAME", "Certainty", "Content Word Accommodation", "Conversational Repair", "Dale-Chall Score", "Discursive Diversity", "Forward Flow", "Function Word Accommodation", "Gini Coefficient", "Hedge", "Features: Conceptual Documentation", "Information Diversity", "Information Exchange", "Linguistic Inquiry and Word Count (LIWC) and Other Lexicons", "Message Length", "Message Quantity", "Mimicry (BERT)", "Moving Mimicry", "Named Entity Recognition", "Online Discussion Tags", "Politeness/Receptiveness Markers", "Politeness Strategies", "Sentiment (RoBERTa)", "Positivity Z-Score", "Proportion of First Person Pronouns", "Question (Naive)", "Team Burstiness", "Textblob Polarity", "Textblob Subjectivity", "Time Difference", "Turn Taking Index", "Word Type-Token Ratio", "The Team Communication Toolkit", "Introduction", "assign_chunk_nums module", "calculate_chat_level_features module", "calculate_conversation_level_features module", "calculate_user_level_features module", "check_embeddings module", "gini_coefficient module", "Utilities", "preload_word_lists module", "preprocess module", "summarize_features module", "zscore_chats_and_conversation module"], "titleterms": {"0": 42, "1": 42, "5": 42, "A": 0, "One": 0, "The": [0, 61, 62], "accommod": [31, 36], "addit": 1, "advanc": 1, "aggreg": [1, 11], "analyz": 1, "assign_chunk_num": 63, "assumpt": 0, "base": 11, "basic": [0, 1, 29, 30, 31, 33, 34, 35, 36, 37, 38, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 56, 57, 58, 59, 60], "basic_featur": 3, "bert": 45, "bring": 42, "bursti": [4, 55], "cach": 1, "calculate_chat_level_featur": 64, "calculate_conversation_level_featur": 65, "calculate_user_level_featur": 66, "caveat": [1, 29, 30, 31, 33, 34, 35, 36, 38, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 56, 57, 58, 59], "certainti": [5, 30], "chall": 33, "chat": [11, 39], "check_embed": 67, "citat": [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60], "class": 69, "code": [0, 1], "coeffici": 37, "column": [1, 61], "commun": 61, "conceptu": 39, "configur": 1, "consider": 1, "content": [31, 61], "convers": [1, 11, 32, 39, 62, 69], "count": [42, 59], "cumul": 1, "custom": [1, 42], "customiz": 0, "dale": 33, "data": 1, "declar": 61, "demo": [0, 1], "detail": 1, "differ": 58, "directori": 1, "discurs": 34, "discursive_divers": 6, "discuss": 48, "divers": [34, 40], "document": [11, 39, 62], "driver": 69, "entiti": [1, 47], "environ": [1, 61], "exampl": [1, 41, 47], "exchang": 41, "featur": [1, 11, 29, 30, 31, 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46, 47, 51], "overview": 1, "own": 42, "packag": [0, 1, 61], "paramet": [0, 1], "percentag": 1, "person": 53, "pip": [1, 61], "polar": 56, "polit": [49, 50], "politeness_featur": 17, "politeness_v2": 18, "politeness_v2_help": 19, "posit": 52, "preload_word_list": 70, "preprocess": 71, "pronoun": 53, "proport": 53, "quantiti": 44, "question": 54, "question_num": 20, "ratio": 60, "readabl": 21, "recept": 49, "recognit": [1, 47], "recommend": [1, 61], "reddit_tag": 22, "regener": 1, "relat": [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60], "repair": 32, "roberta": 51, "run": 1, "sampl": [0, 1], "score": [33, 41, 52], "sentiment": 51, "speaker": [11, 59, 62, 69], "start": [0, 1, 61, 62], "strategi": 50, "subject": 57, "summarize_featur": 72, "tabl": 61, "tag": 48, "take": 59, "team": [55, 61, 62], "technic": 11, "temporal_featur": 23, "textblob": [56, 57], "textblob_sentiment_analysi": 24, "time": 58, "token": 60, "toolkit": 61, "touch": 0, "train": 47, "troubleshoot": [1, 61], "turn": [1, 59], "turn_taking_featur": 25, "type": 60, "us": 61, "usag": 1, "user": 11, "util": 69, "utter": [11, 39, 62, 69], "v": 42, "variance_in_dd": 26, "vector": 1, "virtual": [1, 61], "walkthrough": 1, "within_person_discursive_rang": 27, "word": [31, 36, 42, 60], "word_mimicri": 28, "work": 1, "your": [1, 42], "z": [41, 52], "zscore_chats_and_convers": 73}})
\ No newline at end of file
diff --git a/docs/build/html/utils/calculate_conversation_level_features.html b/docs/build/html/utils/calculate_conversation_level_features.html
index b377c9a3..df109253 100644
--- a/docs/build/html/utils/calculate_conversation_level_features.html
+++ b/docs/build/html/utils/calculate_conversation_level_features.html
@@ -55,10 +55,7 @@
 
                    • Utilities
                        
 
                      • “Driver” Classes: Utterance-, Conversation-, and Speaker-Level Features
 
                        • 
@@ -92,181 +89,8 @@
           
                        
            
                        
              
-  
                        
-
                        calculate_conversation_level_features module
                        
-
                        
-
                        
-class utils.calculate_conversation_level_features.ConversationLevelFeaturesCalculator(chat_data: DataFrame, user_data: DataFrame, conv_data: DataFrame, vect_data: DataFrame, vector_directory: str, conversation_id_col: str, speaker_id_col: str, message_col: str, timestamp_col: str, convo_aggregation: bool, convo_methods: list, convo_columns: list, user_aggregation: bool, user_methods: list, user_columns: list, chat_features: list)
                        
-
                        Bases: object
                        
-
                        Initialize variables and objects used by the ConversationLevelFeaturesCalculator class.
                        
-
                        This class uses various feature modules to define conversation-level features. It reads input data and
-initializes variables required to compute the features.
                        
-
                        
-
                        Parameters:
                        
-
                          
-
                        • chat_data (pd.DataFrame) – Pandas dataframe of chat-level features read from the input dataset
                          • 
-
                        • user_data (pd.DataFrame) – Pandas dataframe of user-level features derived from the chat-level dataframe
                          • 
-
                        • conv_data (pd.DataFrame) – Pandas dataframe of conversation-level features derived from the chat-level dataframe
                          • 
-
                        • vect_data (pd.DataFrame) – Pandas dataframe of processed vectors derived from the chat-level dataframe
                          • 
-
                        • vector_directory (str) – Directory where vector files are stored
                          • 
-
                        • convo_aggregation (bool) – If true, will aggregate features at the conversational level
                          • 
-
                        • convo_methods (list) – Specifies which functions users want to aggregate with (e.g., mean, stdev…)
                          • 
-
                        • convo_columns (list) – Specifies which columns (at the chat level) users want aggregated
                          • 
-
                        • user_aggregation – If true, will aggregate features at the user level
                          • 
-
                        • user_methods (list) – Specifies which functions users want to aggregate with (e.g., mean, stdev…) at the user level
                          • 
-
                        • user_columns (list) – Specifies which columns (at the chat level) users want aggregated for the user level
                          • 
-
                        • chat_features (list) – Tracks all the chat-level features generated by the toolkit
                          • 
-
                        
-
                        
-
                        
-
                        
-
                        
-calculate_conversation_level_features(feature_methods: list) → DataFrame
                        
-
                        Main driver function for creating conversation-level features.
                        
-
                        This function computes various conversation-level features by aggregating chat-level and user-level features,
-and appends them as new columns to the input conversation-level data.
                        
-
                        
-
                        Parameters:
                        
-
                        feature_methods – The list of methods to use to generate features
                        
-
                        
-
                        Returns:
                        
-
                        The conversation-level dataset with new columns for each conversation-level feature
                        
-
                        
-
                        Return type:
                        
-
                        pd.DataFrame
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-calculate_info_diversity() → None
                        
-
                        Calculate an information diversity score for the team.
                        
-
                        This function computes the information diversity score by looking at the cosine
-similarity between the mean topic vector of the team and each message’s topic vectors,
-and merges the results into the conversation-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-calculate_team_burstiness() → None
                        
-
                        Calculate the team burstiness coefficient.
                        
-
                        This function computes the team burstiness coefficient by looking at the differences
-in standard deviation and mean of the time intervals between chats, and merges the
-results into the conversation-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_conversation_level_aggregates() → None
                        
-
                        Aggregate summary statistics from chat-level features to conversation-level features.
                        
-
                        This function calculates and merges the following aggregation functions for each summarizable feature:
-- Average/Mean
-- Standard Deviation
-- Minimum
-- Maximum
                        
-
                        For countable features (e.g., num_words, num_chars, num_messages), it also calculates and merges the sum.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_discursive_diversity_features() → None
                        
-
                        Calculate discursive diversity features for each conversation.
                        
-
                        This function computes discursive diversity based on the word embeddings (SBERT)
-and chat-level information, and merges the features into the conversation-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_gini_features() → None
                        
-
                        Calculate the Gini index for relevant features in the conversation.
                        
-
                        This function computes the Gini index for features involving counts, such as:
-- Word count
-- Character count
-- Message count
                        
-
                        The Gini index is then merged into the conversation-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_turn_taking_features() → None
                        
-
                        Calculate the turn-taking index in the conversation.
                        
-
                        This function merges turn-taking features into the conversation-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_user_level_aggregates() → None
                        
-
                        Aggregate summary statistics from user-level features to conversation-level features.
                        
-
                        This function calculates and merges the following aggregation functions for each user-level feature:
-- Average/Mean of summed user-level features
-- Standard Deviation of summed user-level features
-- Minimum of summed user-level features
-- Maximum of summed user-level features
-- Average/Mean of averaged user-level features
-- Standard Deviation of averaged user-level features
-- Minimum of averaged user-level features
-- Maximum of averaged user-level features
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
+  
                        
+
                        calculate_conversation_level_features module
                        
 
                        
 
 
diff --git a/docs/build/html/utils/calculate_user_level_features.html b/docs/build/html/utils/calculate_user_level_features.html
index a8a17750..3b57c3f2 100644
--- a/docs/build/html/utils/calculate_user_level_features.html
+++ b/docs/build/html/utils/calculate_user_level_features.html
@@ -56,10 +56,7 @@
 
                      • “Driver” Classes: Utterance-, Conversation-, and Speaker-Level Features
 
                        • 
 
                      • Other Utilities
                        • 
@@ -92,110 +89,8 @@
           
                        
            
                        
              
-  
                        
-
                        calculate_user_level_features module
                        
-
                        
-
                        
-class utils.calculate_user_level_features.UserLevelFeaturesCalculator(chat_data: DataFrame, user_data: DataFrame, vect_data: DataFrame, conversation_id_col: str, speaker_id_col: str, user_aggregation: bool, user_methods: list, user_columns: list, chat_features: list)
                        
-
                        Bases: object
                        
-
                        Initialize variables and objects used by the UserLevelFeaturesCalculator class.
                        
-
                        This class uses various feature modules to define user- (speaker) level features. It reads input data and
-initializes variables required to compute the features.
                        
-
                        
-
                        Parameters:
                        
-
                          
-
                        • chat_data (pd.DataFrame) – Pandas dataframe of chat-level features read from the input dataset
                          • 
-
                        • user_data (pd.DataFrame) – Pandas dataframe of user-level features derived from the chat-level dataframe
                          • 
-
                        • vect_data (pd.DataFrame) – Pandas dataframe of message embeddings corresponding to each instance of the chat data
                          • 
-
                        • conversation_id_col (str) – A string representing the column name that should be selected as the conversation ID. Defaults to “conversation_num”.
                          • 
-
                        • speaker_id_col (str) – A string representing the column name that should be selected as the speaker ID. Defaults to “speaker_nickname”.
                          • 
-
                        • user_aggregation (bool) – If true, will aggregate features at the user level
                          • 
-
                        • user_methods (list) – Specifies which functions users want to aggregate with (e.g., mean, stdev…) at the user level
                          • 
-
                        • user_columns (list) – Specifies which columns (at the chat level) users want aggregated for the user level
                          • 
-
                        • chat_features (list) – Tracks all the chat-level features generated by the toolkit
                          • 
-
                        
-
                        
-
                        
-
                        
-
                        
-calculate_user_level_features() → DataFrame
                        
-
                        Main driver function for creating user-level features.
                        
-
                        This function computes various user-level features by aggregating chat-level data,
-and appends them as new columns to the input user-level data.
                        
-
                        
-
                        Returns:
                        
-
                        The user-level dataset with new columns for each user-level feature
                        
-
                        
-
                        Return type:
                        
-
                        pd.DataFrame
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_centroids() → None
                        
-
                        Calculate the centroid of each user’s chats in a given conversation for future discursive metric calculations.
                        
-
                        This function computes and appends the mean embedding (centroid) of each user’s chats to the user-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_user_level_summary_statistics_features() → None
                        
-
                        This function is used to aggregate the summary statistics from
-chat level features to user level features.
                        
-
                        There are many possible ways to aggregate user level features, e.g.:
-- Mean of all chats by a given user;
-- Max of all chats by a given user;
-- Weighted mean (e.g., looking at different time points?)
-… and so on.
                        
-
                        This is an open question, so we are putting a TODO here.
                        
-
                        
-
-
                        
-
                        
-get_user_level_summed_features() → None
                        
-
                        Aggregate summary statistics from chat-level features that need to be summed together.
                        
-
                        Features for which summing makes sense include:
-- Word count (total number of words)
-- Character count
-- Message count
                        
-
                        This function calculates and merges the summed features into the user-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
                        
-get_user_network() → None
                        
-
                        Get the user list per user per conversation.
                        
-
                        This function calculates and appends the list of other users in a given conversation to the user-level data.
                        
-
                        
-
                        Returns:
                        
-
                        None
                        
-
                        
-
                        Return type:
                        
-
                        None
                        
-
                        
-
                        
-
                        
-
-
                        
-
+  
                        
+
                        calculate_user_level_features module
                        
 
                        
 
 
diff --git a/docs/build/html/utils/check_embeddings.html b/docs/build/html/utils/check_embeddings.html
index e3a078df..d50ae20f 100644
--- a/docs/build/html/utils/check_embeddings.html
+++ b/docs/build/html/utils/check_embeddings.html
@@ -71,6 +71,7 @@
 
                      • is_valid_term()
                        • 
 
                      • load_liwc_dict()
                        • 
 
                      • read_in_lexicons()
                        • 
+
                      • sort_words()
                        • 
 
                      • str_to_vec()
                        • 
 
                      
 
                      • 
@@ -275,27 +276,28 @@
 
 
                      
 
                      
-utils.check_embeddings.is_valid_term(dicTerm)
                      
+utils.check_embeddings.is_valid_term(dicTerm: str) → bool
 
                      Check if a dictionary term is valid.
                      
-
                      This function returns True if the term matches the regex pattern and False otherwise.
-The regex pattern matches:
                      
-
                        
-
                      • Alphanumeric characters (a-z, A-Z, 0-9)
                        • 
-
                      • Valid symbols: -, ‘, *, /
                        • 
-
                      • The * symbol can appear only once at the end of a word
                        • 
-
                      • Emojis are valid only when they appear alone
                        • 
-
                      • The / symbol can appear only once after alphanumeric characters
                        • 
-
                      • Spaces are allowed between valid words
                        • 
-
                      
+
                      This functions returns True if the term matches the regex pattern and Flase otherwise.
+The regex pattern matches:
+- Alphanumeric characters (a-zA-Z0-9)
+- Valid symbols: -, ‘, *, /
+- The * symbol can only appear once at the end of a word
+- 8 emojis are valid only when they appear alone
+- The / symbol can only appear once after alphanumeric characters
+- Spaces are allowed between valid words
                      
 
                      
 
                      Parameters:
                      
-
                      dicTerm (str) – The dictionary term to validate.
                      
+
                      dicTerm (str) – The dictionary term
                      
 
                      
-
                      Returns:
                      
-
                      True if the term is valid, False otherwise.
                      
+
                      
+
                      hi:) 120
                      
+
                      
+
                      Returns:
                      
+
                      True/False
                      
 
                      
-
                      Return type:
                      
-
                      bool
                      
+
                      Return type:
                      
+
                      bool
                      
 
                      
 
                      
 
                      
@@ -308,7 +310,18 @@
 
                      This functions reads the content of a LIWC dictionary file in the official format,
 and convert it to a dictionary with lexicon: regular expression format.
 We assume the dicText has two parts: the header, which maps numbers to “category names,”
-and the body, which maps words in the lexicon to different category numbers, separated by a ‘%’ sign.
                      
+and the body, which maps words in the lexicon to different category numbers, separated by ‘%’.
+Below is an example:
+‘’’
+%
+1   function
+2   pronoun
+3   ppron
+%
+again       1       2
+against     1       2       3
+‘’’
+Note that the elements in each line are separated by ‘      ‘.
                      
 
                      
 
                      Parameters:
                      
 
                      dicText (str) – The content of a .dic file
                      
@@ -327,6 +340,25 @@
 utils.check_embeddings.read_in_lexicons(directory, lexicons_dict)
 
                      
 
+
                      
+
                      
+utils.check_embeddings.sort_words(lexicons: list) → str
                      
+
                      Sorts the dictionary terms in a list.
                      
+
                      This function sorts the dictionary terms in a list by their length in descending order.
+The hyphenated words are sorted first, followed by the non-hyphenated words.
                      
+
                      
+
                      Parameters:
                      
+
                      dicTerms (list) – List of dictionary terms
                      
+
                      
+
                      Returns:
                      
+
                      dicTerms
                      
+
                      
+
                      Return type:
                      
+
                      str
                      
+
                      
+
                      
+
                      
+
 
                      
 
                      
 utils.check_embeddings.str_to_vec(str_vec)
                      
diff --git a/docs/source/features_conceptual/liwc.rst b/docs/source/features_conceptual/liwc.rst
index fb0c2d3b..04a4ff77 100644
--- a/docs/source/features_conceptual/liwc.rst
+++ b/docs/source/features_conceptual/liwc.rst
@@ -20,6 +20,14 @@ Positive Word Lexicon: `Hu and Liu (2004)
  • Introduction