Digital Acceleration, Operational Inertia: Computational Mining of Grey Literature in Global Earthquake Response
This is the open research companion to a study analyzing 40 years of global earthquake response data (1985–2025) through computational mining of grey literature (UN-OCHA ReliefWeb API harvest, USGS seismic catalog integration, LDA topic modeling, and KDE reporting latency analysis).
⚠️ Status: Under Peer Review The manuscript is currently under peer review. No article DOI or publisher Version of Record (VoR) has been assigned yet. This repository serves as an open research companion containing analytical code, author-generated figures, parameter tables, and harvesting scripts—it does not contain manuscript text drafts, publisher PDFs, or third-party geospatial raw datasets.
| -0.5 days/yr Mean latency trend, 1985–2025 |
11 Reports Global Flagship DRR Corpus |
20 Events Anchor Earthquakes Analyzed |
4 Topics LDA Semantic Clusters |
ROSES Evidence Synthesis Protocol |
flowchart LR
A["ReliefWeb API Harvest<br>+ USGS Seismic Catalog"] --> B["Dual Corpus Design<br>(11 Flagship & 20 Anchor Events)"]
B --> C["KDE Reporting Latency<br>& Linear Regression"]
B --> D["LDA Topic Modeling<br>(4 Operational Clusters)"]
C --> E["Digital Acceleration vs.<br>Operational Inertia"]
D --> E
E --> F["Build vs. Fuel Trap &<br>Paper Tigers Diagnosis"]
Detailed mathematical definitions and methodology are documented in docs/methodology.md.
To run the pipeline and verify code integrity locally:
# 1. Clone repository
git clone https://github.com/YusufEminoglu/earthquake-grey-lit-response.git
cd earthquake-grey-lit-response
# 2. Environment setup
conda env create -f environment.yml
conda activate greylit-env
# 3. Verify integrity audit
python scripts/publication_audit.py| Figure 1: ROSES Methodology | Figure 2: Geographic & Temporal Extent |
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| Figure 3: Spatial Map & Anchor Events | Figure 4: Global Institutional Landscape |
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| Figure 5: Semantic Word Cloud Clusters | Figure 6: Topic Prevalence Streamgraph |
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| Figure 7: Implementation Gap Matrix | Figure 8: Longitudinal Latency & KDE |
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This repository prioritizes reproducibility of analysis logic and figures while respecting third-party dataset terms:
- Code & Table Reproducibility: Harvesting scripts, LDA parameter tables, KDE trend metrics, and authored figures are fully contained.
- Raw Spatial/APIs: Raw API queries (ReliefWeb, USGS) can be executed dynamically via
src/python/01_get_earthquake_disasters.py. See docs/data_inventory.md.
| Author | Affiliation | Contact & Profiles |
|---|---|---|
| Yusuf Eminoğlu · corresponding author | Department of City and Regional Planning, Dokuz Eylül University; LUQAA — Lab of Urban Analytics and Quantitative Analysis |    |
| Prof. Dr. Hilmi Evren Erdin | Department of City and Regional Planning, Dokuz Eylül University, İzmir, Türkiye |   |
If you use this codebase or software components, please refer to CITATION.cff.
- Code: MIT License
- Figures & Documentation: CC BY 4.0
humanitarian-information-management · disaster-risk-reduction · grey-literature-mining · reliefweb-api · usgs-earthquake · urban-resilience · lda-topic-modeling · kernel-density-estimation · roses-protocol · seismic-hazard