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Using past violence and current news to predict changes in violence

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  • Hannes Mueller
  • Christopher Rauh

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.Este artículo propone un nuevo método para la predicción de escaladas y desescaladas de violencia a través de la aplicación de un modelo basado en los antecedentes del conflicto y las características propias del texto. Las características del texto se generan a partir de más de 3,5 millones de artículos de periódicos mediante el uso de lo que se denomina “modelo de tópicos”. Demostramos que, si bien este modelo combinado hace referencia a una extensa dinámica del conflicto, el texto es una contribución relevante que permite predecir los estallidos de violencia inesperados en países que antes eran pacíficos. Dada la dinámica de gran intensidad característica de la trampa del conflicto, estos casos son de especial importancia en lo que se refiere a las iniciativas de prevención.Dans cet article, nous proposons une nouvelle méthode destinée à anticiper les escalades et désescalades de violence grâce à un modèle reposant sur les antécédents conflictuels et sur des caractéristiques textuelles. Ces caractéristiques sont extraites à partir de plus de 3,5 millions d’articles de presse à l’aide d’un modèle thématique (topic model). Nous montrons que si ce modèle mixte s’appuie largement sur les dynamiques conflictuelles, les données textuelles peuvent être très utiles en vue d’anticiper les rares explosions de violence dans les pays habituellement pacifiques. Étant donné la puissante dynamique qui sous-tend les conflits récurrents, les exemples exposés revêtent une importance particulière dans une optique de prévention.

Suggested Citation

  • Hannes Mueller & Christopher Rauh, 2022. "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 579-596, July.
  • Handle: RePEc:taf:ginixx:v:48:y:2022:i:4:p:579-596
    DOI: 10.1080/03050629.2022.2063853
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    1. Mueller, Hannes & Rauh, Christopher, 2018. "Reading Between the Lines: Prediction of Political Violence Using Newspaper Text," American Political Science Review, Cambridge University Press, vol. 112(2), pages 358-375, May.
    2. Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
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    1. Diakonova, Marina & Ghirelli, Corinna & Molina, Luis & Pérez, Javier J., 2023. "The economic impact of conflict-related and policy uncertainty shocks: The case of Russia," International Economics, Elsevier, vol. 174(C), pages 69-90.

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    More about this item

    JEL classification:

    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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