2025/06/23 by Sebastian Haunss, Priska Daphi, Jan Matti Dollbaum +3 · 1 voice
Computer Science · #Network Security and Intrusion Detection
paper · pdf · doi:10.1017/psrm.2025.10013
openalex publication_date 2025/06/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
Abstract Protest event analysis (PEA) is the core method to understand spatial patterns and temporal dynamics of protest. We show how Large Language Models (LLM) can be used to automate the classification of protest events and of political event data more broadly with levels of accuracy comparable to humans, while reducing necessary annotation time by several orders of magnitude. We propose a modular pipeline for the automation of PEA (PAPEA) based on fine-tuned LLMs and provide publicly available models and tools which can be easily adapted and extended. PAPEA enables getting from newspaper articles to PEA datasets with high levels of precision without human intervention. A use case based on a large German news-corpus illustrates the potential of PAPEA.