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Reading Between the Lines: Prediction of Political Violence Using Newspaper Text

Author

Listed:
  • Hannes Mueller
  • Christopher Rauh

Abstract

This article provides a new methodology to predict armed conflict by using newspaper text. Through machine learning, vast quantities of newspaper text are reduced to interpretable topics. These topics are then used in panel regressions to predict the onset of conflict. We propose the use of the within-country variation of these topics to predict the timing of conflict. This allows us to avoid the tendency of predicting conflict only in countries where it occurred before. We show that the within-country variation of topics is a good predictor of conflict and becomes particularly useful when risk in previously peaceful countries arises. Two aspects seem to be responsible for these features. Topics provide depth because they consist of changing, long lists of terms which makes them able to capture the changing context of conflict. At the same time topics provide width because they are summaries of the full text, including stabilizing factors.

Suggested Citation

  • Hannes Mueller & Christopher Rauh, 2017. "Reading Between the Lines: Prediction of Political Violence Using Newspaper Text," Working Papers 990, Barcelona Graduate School of Economics.
  • Handle: RePEc:bge:wpaper:990
    as

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    References listed on IDEAS

    as
    1. Hannes Mueller, 2016. "Growth and Violence: Argument for a Per Capita Measure of Civil War," Economica, London School of Economics and Political Science, vol. 83(331), pages 473-497, July.
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    Citations

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    Cited by:

    1. Toke S. Aidt, Facundo Albornoz, Esther Hauk & Facundo Albornoz & Esther Hauk, 2019. "Foreign in influence and domestic policy: A survey," Cambridge Working Papers in Economics 1928, Faculty of Economics, University of Cambridge.
    2. Bazzi, Samuel & Blair, Robert & Blattman, Christopher & Dube, Oeindrila & Gudgeon, Matthew & Peck, Richard, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," CEPR Discussion Papers 13829, C.E.P.R. Discussion Papers.
    3. Toke S. Aidt & Facundo Albornoz & Esther Hauk, 2019. "Foreign influence and domestic policy," Discussion Papers 2019-03, University of Nottingham, GEP.
    4. Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
    5. Jesús Rodríguez-López & Mario Solís-García, 2018. "Defense spending and fiscal multipliers: it's all in the variance," Working Papers 18.06, Universidad Pablo de Olavide, Department of Economics.

    More about this item

    Keywords

    Civil War; conflict; early-warning; topic model; forecasting; machine learning; news; prediction; panel regression;

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth

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