Using Past Violence and Current News to Predict Changes in Violence

Hannes Mueller and Christopher Rauh

Janeway Institute Working Papers from Faculty of Economics, University of Cambridge

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: Conflict; prediction; machine learning; LDA; topic model; battle deaths; ViEWS prediction competition; random forest (search for similar items in EconPapers)
JEL-codes: C53 C55 F21 (search for similar items in EconPapers)
Date: 2022-03-22
New Economics Papers: this item is included in nep-ban, nep-big and nep-cmp
Note: cr542
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Working Paper: Using Past Violence and Current News to Predict Changes in Violence (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camjip:2209

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