Feb. 5, 2024, 3:45 p.m. | Mihai Croicu

stat.ML updates on arXiv.org arxiv.org

High-resolution event data on armed conflict and related processes have revolutionized the study of political contention with datasets like UCDP GED, ACLED etc. However, most of these datasets limit themselves to collecting spatio-temporal (high-resolution) and intensity data. Information on dynamics, such as targets, tactics, purposes etc. are rarely collected owing to the extreme workload of collecting data. However, most datasets rely on a rich corpus of textual data allowing further mining of further information connected to each event. This paper …

active learning conflict cs.cl cs.cy data data mining datasets dynamics etc event information intensity mining political processes stat.ml study tactics targets temporal text

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