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Introducing a Global Dataset on Conflict Forecasts and News Topics

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  • Mueller, H.
  • Rauh, C.
  • Seimon, B.

Abstract

This article provides a structured description of openly available news topics and forecasts for armed conflict at the national and grid cell level starting January 2010. The news topics as well as the forecasts are updated monthly at conflictforecast.org and provide coverage for more than 170 countries and about 65,000 grid cells of size 55x55km worldwide. The forecasts rely on Natural Language Processing (NLP) and machine learning techniques to leverage a large corpus of newspaper text for predicting sudden onsets of violence in peaceful countries. Our goals are to: a) support conflict prevention efforts by making our risk forecasts available to practitioners and research teams worldwide, b) facilitate additional research that can utilise risk forecasts for causal identification, and to c) provide an overview of the news landscape.

Suggested Citation

  • Mueller, H. & Rauh, C. & Seimon, B., 2024. "Introducing a Global Dataset on Conflict Forecasts and News Topics," Cambridge Working Papers in Economics 2404, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:2404
    Note: cr542
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    References listed on IDEAS

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    1. Dominic Rohner & Mathias Thoenig, 2021. "The Elusive Peace Dividend of Development Policy: From War Traps to Macro Complementarities," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 111-131, August.
    2. Paola Vesco & Håvard Hegre & Michael Colaresi & Remco Bastiaan Jansen & Adeline Lo & Gregor Reisch & Nils B. Weidmann, 2022. "United they stand: Findings from an escalation prediction competition," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 860-896, July.
    3. Alessandro Ruggieri & Hannes Mueller, 2022. "Dynamic Early Warning and Action Model," Working Papers 1355, Barcelona School of Economics.
    4. Håvard Hegre & Paola Vesco & Michael Colaresi, 2022. "Lessons from an escalation prediction competition," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 521-554, July.
    5. Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2022. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 764-779, October.
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    Cited by:

    1. Diakonova, Marina & Molina, Luis & Mueller, Hannes & Pérez, Javier J. & Rauh, Christopher, 2024. "The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(4).

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