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Mueller, H. and Rauh, C.

Using Past Violence and Current News to Predict Changes in Violence

International Interactions

(2022)

Abstract: This article proposes a new method for predicting escalations and de-escalations of violence using a model which relies on conflict history and text features. The text features are generated from over 3.5 million newspaper articles using a so-called topic-model. We show that the combined model relies to a large extent on conflict dynamics, but that text is able to contribute meaningfully to the prediction of rare outbreaks of violence in previously peaceful countries. Given the very powerful dynamics of the conflict trap these cases are particularly important for prevention efforts

Keywords: Armed conflict, civil war, forecasting, machine learning, text analysis

JEL Codes: F21, C53, C55

Author links: Christopher Rauh  

Publisher's Link: https://doi.org/10.1080/03050629.2022.2063853



Cambridge-INET Working Paper Version of Paper: Using Past Violence and Current News to Predict Changes in Violence, Mueller, H., Rauh, C. , (2022)