Mapping Violent Presence of Armed Actors in Colombia

Abstract. Heat maps and Early Warning Systems have traditionally contributed to identifying and managing risks associated with crime trends, health hazards, and natural disasters. However, their application to analyzing civil war dynamics still is at an early stage. To address this need, this research integrates Natural Language Processing (NLP) tools and Geographic Information Systems (GIS) to generate an interactive map of the violent presence of armed actors in the Colombian civil war between 1988 and 2017. The NLP component generates fine-grained geo-location data of armed actors' violent presence. The GIS component then uses the geo-referenced data to present dynamic clusters of four main types of actors: Government forces, Insurgent organizations, Paramilitary groups, and Criminal organizations. Each type of actors is further disaggregated into a multitude of specific armed organizations. Based on anomalies in the spatio-temporal trends identified in the data, we develop an EWS methodology to detect “emerging”, “intense”, and “critical” cases. This application contributes to the efforts of the academic and policy communities to understanding the spatio-temporal dynamics of political violence and promoting sustainable peace in civil war settings.