摘要：colombia experienced a decades-long civil war between the government and many left-wingguerrilla groups.It was marked by violence, kidnappings, and large quantities of humandisplacement. Monitoring and forecasting civil wars are important to mitigate their potentialimpact but require access to ground truth data.We examine the use of Internet data streams,namely Google search queries, tweets related to politics, and traditional news sources toretrospectively forecast(i.e., hindcast) state-based armed violence in Colombia. We comparethe results of statistical models using three combinations of these features to evaluate thepredictive capabilities of each data stream.Our results show that the combination of Internetand traditional news data models perform most consistently, although Internet-only issurprisingly promising.Overall, we are able to produce high-quality models hindcasting thepresence or absence of state-based armed violence in Colombia up to 6 months in advance.These results support the use of exogenous data streams to forecast evolving situationsaround the globe.
