Using Past Violence and Current News to Predict Changes in Violence
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Authors
Mueller, H.
Rauh, C.
Publication Date
2022-03-22Series
Cambridge Working Papers in Economics
Janeway Institute Working Paper Series
Publisher
Faculty of Economics, University of Cambridge
Type
Working Paper
Metadata
Show full item recordCitation
Mueller, H., & Rauh, C. (2022). Using Past Violence and Current News to Predict Changes in Violence. https://doi.org/10.17863/CAM.83983
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
Identifiers
CWPE2220, JIWP2209
This record's DOI: https://doi.org/10.17863/CAM.83983
This record's URL: https://www.repository.cam.ac.uk/handle/1810/336562
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