Geolocating Political Events in Text

Abstract

This work introduces a general method for automatically finding the locations where political events in text occurred. Using a novel set of 8,000 labeled sentences, I create a method to link automatically extracted events and locations in text. The model achieves human level performance on the annotation task and outperforms previous event geolocation systems. It can be applied to most event extraction systems across geographic contexts. I formalize the event–location linking task, describe the neural network model, describe the potential uses of such a system in political science, and demonstrate a workflow to answer an open question on the role of conventional military offensives in causing civilian casualties in the Syrian civil war.

Publication
Proceedings of the Third Workshop on Natural Language Processing and Computational Social Science, NAACL
Andy Halterman
Andy Halterman
PhD Candidate

My research interests include natural language processing, text as data, and subnational armed conflict

Related