Interpretable ML project combining Global Terrorism Database event records with international news framing to analyze terrorism severity rankings, residuals, and feature importance.
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Updated
May 2, 2026 - Python
Interpretable ML project combining Global Terrorism Database event records with international news framing to analyze terrorism severity rankings, residuals, and feature importance.
Comparative analysis of how domestic Ethiopian and Western media framed the Tigray conflict (2020-2022), with data and reproducible methods.
Zero-shot news framing classifier (BART-MNLI) validated with an independent LLM judge across Reuters, Fox News, and Politico articles. Includes a documented case study of where zero-shot labeling breaks down.
Media framing of 4chan in Canadian government-funded media (2015-2025) — a reproducible BERTopic pipeline
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