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

Published online by Cambridge University Press:  14 December 2017

HANNES MUELLER  and
CHRISTOPHER RAUH
HANNES MUELLER*
Affiliation:
Institut d’Analisi Economica
CHRISTOPHER RAUH*
Affiliation:
University of Montreal
*
Hannes Mueller is a tenured scientist at IAE (CSIC), Barcelona GSE Institut d’Analisi Economica, CSIC Campus UAB, 08193Bellaterra, Spain ([email protected]).
Christopher Rauh is an Assistant Professor at University of Montreal, Département de Sciences Économiques, Université de Montréal, C.P.6128 succ. Centre-Ville, Montréal H3C 3J7, Canada ([email protected]).
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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 that make 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.

Type
Research Article
Information
American Political Science Review , Volume 112 , Issue 2 , May 2018 , pp. 358 - 375
Copyright
Copyright © American Political Science Association 2017 

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Footnotes

We thank Tim Besley, Melissa Dell, Vincenzo Galasso, Hector Galindo, Matt Gentzkow, Stephen Hansen, Ethan Kapstein, Daniel Ohayon, Akash Raja, Bernhard Reinsberg, Anand Shrivastava, Ron Smith, Jack Willis, Stephane Wolton, and the participants of the workshops and conferences ENCoRe Barcelona, Political Economy Cambridge (internal), EPCS Freiburg, ESOC in Washington, Barcelona GSE Calvo-Armengol, NBER SI Economics of National Security, Conflict at IGIER, and the seminars PSPE at LSE, BBE at WZB, and Macro Lunch Cambridge for valuable feedback. We are grateful to Alex Angelini, Lavinia Piemontese, and Bruno Conte Leite for excellent research assistance. We thank the Barcelona GSE under the Severo Ochoa Programme for financial assistance. All errors are ours.

References

REFERENCES

Bazzi, Samuel, and Blattman, Christopher. 2014. “Economic Shocks and Conflict: Evidence from Commodity Prices.” American Economic Journal: Macroeconomics 6 (4): 1–38.Google Scholar
Beck, Nathaniel. 2015. “Estimating Grouped Data Models with a Binary Dependent Variable and Fixed Effects: What Are the Issues?” Annual Meeting of the Society for Political Methodology, July.Google Scholar
Belloni, Alexandre, Chernozhukov, Victor, Hansen, Christian et al. 2011. “Inference for High-Dimensional Sparse Econometric Models.” Centre for Microdata Methods and Practice, Institute for Fiscal Studies.Google Scholar
Besley, Timothy, and Persson, Torsten. 2011 a. “The Logic of Political Violence.” Quarterly Journal of Economics 126 (3): 1411–45.Google Scholar
Besley, Timothy, and Persson, Torsten. 2011 b. Pillars of Prosperity: The Political Economics of Development Clusters. Princeton, NJ: Princeton University Press.Google Scholar
Blattman, Christopher, Hartman, Alexandra C., and Blair, Robert A.. 2014. “How to Promote Order and Property Rights Under Weak Rule of Law? An Experiment in Changing Dispute Resolution Behavior through Community Education.” American Political Science Review 108 (01): 100–20.Google Scholar
Blattman, Christopher, and Miguel, Edward. 2010. “Civil War.” Journal of Economic Literature 48 (1): 3–57.Google Scholar
Blei, David M., and Lafferty, John D.. 2006. “Dynamic Topic Models.” In Proceedings of the 23rd International Conference on Machine Learning. ACM, pp. 113–20.Google Scholar
Blei, David M., Ng, Andrew Y. and Jordan, Michael I.. 2003. “Latent Dirichlet Allocation.” The Journal of Machine Learning Research 3: 993–1022.Google Scholar
Brandt, Patrick T., Freeman, John R., and Schrodt, Philip A.. 2011. “Real Time, Time Series Forecasting of Inter-And Intra-State Political Conflict.” Conflict Management and Peace Science 28 (1): 41–64.CrossRefGoogle Scholar
Brückner, Markus, and Ciccone, Antonio. 2010. “International Commodity Prices, Growth and the Outbreak of Civil War in Sub-Saharan Africa.” The Economic Journal 120 (544): 519–34.CrossRefGoogle Scholar
Buhaug, Halvard, Nordkvelle, J., Bernauer, T., Böhmelt, T., Brzoska, M., Busby, J. W., Ciccone, A., Fjelde, Hanne, Gartzke, E., Gleditsch, N.P. et al. 2014. “One Effect to Rule them all? A Comment on Climate and Conflict.” Climatic Change 127 (3–4): 391–7.Google Scholar
Caselli, Francesco, and Coleman, Wilbur John. 2013. “On the Theory of Ethnic Conflict.” Journal of the European Economic Association 11 (s1): 161–92.Google Scholar
Cederman, Lars-Erik, and Weidmann, Nils B.. 2017. “Predicting Armed Conflict: Time to Adjust our Expectations?” Science 355 (6324): 474–6.CrossRefGoogle ScholarPubMed
Chadefaux, Thomas. 2014. “Early Warning Signals for War in the News.” Journal of Peace Research 51 (1): 5–18.CrossRefGoogle Scholar
Chadefaux, Thomas. 2017 a. “Conflict Forecasting and its Limits.” Data Science (Preprint): 1–11.CrossRefGoogle Scholar
Chadefaux, Thomas. 2017 b. “Market Anticipations of Conflict Onsets.” Journal of Peace Research 54 (2): 313–27.CrossRefGoogle Scholar
Chiba, Daina, and Gleditsch, Kristian Skrede. 2017. “The Shape of Things to Come? Expanding the Inequality and Grievance Model for Civil War Forecasts with Event Data.” Journal of Peace Research 54 (2): 275–97.CrossRefGoogle Scholar
Collier, Paul, and Hoeffler, Anke. 2004. “Greed and Grievance in Civil War.” Oxford Economic Papers 56 (4): 563–95.CrossRefGoogle Scholar
Collier, Paul, Hoeffler, Anke, and Rohner, Dominic. 2009. “Beyond Greed and Grievance: Feasibility and Civil War.” Oxford Economic Papers 61 (1): 1–27.Google Scholar
Dell, Melissa, Jones, Benjamin F., and Olken, Benjamin A.. 2012. “Temperature Shocks and Economic Growth: Evidence from the Last Half Century.” American Economic Journal: Macroeconomics 4 (3): 66–95.Google Scholar
Esteban, Joan, Mayoral, Laura, and Ray, Debraj. 2012. “Ethnicity and Conflict: An Empirical Study.” The American Economic Review 102 (4): 1310–42.Google Scholar
Fearon, James D. and Laitin, David D.. 2003. “Ethnicity, Insurgency, and Civil War.” American Political Science Review 97 (01): 75–90.Google Scholar
Gerner, Deborah J., Schrodt, Philip A., Yilmaz, Omur, and Abu-Jabr, Rajaa. 2002. “The Creation of CAMEO (Conflict and Mediation Event Observations): An Event Data Framework for a Post Cold War World.” Annual Meeting of the American Political Science Association.Google Scholar
Gleditsch, Kristian Skrede, and Ruggeri, Andrea. 2010. “Political Opportunity Structures, Democracy, and Civil War.” Journal of Peace Research 47 (3): 299–310.CrossRefGoogle Scholar
Gleditsch, Nils Petter, Wallensteen, Peter, Eriksson, Mikael, Sollenberg, Margareta, and Strand, Håvard. 2002. “Armed Conflict 1946–2001: A New Dataset.” Journal of Peace Research 39 (5): 615–37.Google Scholar
Goldstone, Jack A., Bates, Robert H., Epstein, David L., Gurr, Ted Robert, Lustik, Michael B., Marshall, Monty G., Ulfelder, Jay, and Woodward, Mark. 2010. “A Global Model for Forecasting Political Instability.” American Journal of Political Science 54 (1): 190–208.Google Scholar
Hansen, Stephen, McMahon, Michael, and Prat, Andrea. 2014. “Transparency and Deliberation within the FOMC: A Computational Linguistics Approach.” CEP Discussion Paper No. 1276.Google Scholar
Hegre, Håvard, Karlsen, Joakim, Nygård, Håvard Mokleiv, Strand, Håvard, and Urdal, Henrik. 2013. “Predicting Armed Conflict, 2010–20501.” International Studies Quarterly 57 (2): 250–70.Google Scholar
Hegre, Håvard, Metternich, Nils W., Nygård, Håvard Mokleiv, and Wucherpfennig, Julian. 2017. “Introduction: Forecasting in Peace Research.” Journal of Peace Research 54 (2): 113–24.Google Scholar
Kalyvas, Stathis N. and Balcells, Laia. 2010. “International System and Technologies of Rebellion: How the End of the Cold War Shaped Internal Conflict.” American Political Science Review 104 (03): 415–29.Google Scholar
Margolis, J. Eli. 2012. “Estimating State Instability.” Studies in Intelligence 56 (1): 13–24.Google Scholar
Meernik, James. 2005. “Justice and Peace? How the International Criminal Tribunal Affects Societal Peace in Bosnia.” Journal of Peace Research 42 (3): 271–89.Google Scholar
Miguel, Edward, and Satyanath, Shanker. 2011. “Re-examining Economic Shocks and Civil Conflict.” American Economic Journal: Applied Economics 3 (4): 228–32.Google Scholar
Miguel, Edward, Satyanath, Shanker, and Sergenti, Ernest. 2004. “Economic Shocks and Civil Conflict: An Instrumental Variables Approach.” Journal of Political Economy 112 (4): 725–53.Google Scholar
Nimark, Kristoffer P. and Pitschner, Stefan. 2016. “Delegated Information Choice.” No 11323, CEPR Discussion Papers.Google Scholar
Olsen, Tricia D., Payne, Leigh A., and Reiter, Andrew G.. 2010. “Transitional Justice in the World, 1970–2007: Insights from a New Dataset.” Journal of Peace Research 47 (6): 803–9.Google Scholar
Pettersson, Therése, and Wallensteen, Peter. 2015. “Armed Conflicts, 1946–2014.” Journal of Peace Research 52 (4): 536–50.Google Scholar
Phan, Xuan-Hieu, and Nguyen, Cam-Tu. 2007. “GibbsLDA++: AC/C++ Implementation of Latent Dirichlet Allocation (LDA).” URL: http://gibbslda.sourceforge.netGoogle Scholar
Porter, Martin F. 1980. “An Algorithm for Suffix Stripping.” Program 14 (3): 130–7.Google Scholar
Quinn, Kevin M., Monroe, Burt L., Colaresi, Michael, Crespin, Michael H., and Radev, Dragomir R.. 2010. “How to Analyze Political Attention with Minimal Assumptions and Costs.” American Journal of Political Science 54 (1): 209–28.Google Scholar
Reynal-Querol, Marta, and Montalvo, Jose G.. 2005. “Ethnic Polarization, Potential Conflict and Civil War.” American Economic Review 95 (3): 796–816.Google Scholar
Roberts, Margaret E., Stewart, Brandon M., Tingley, Dustin, Airoldi, Edoardo M., et al. 2013. “The Structural Topic Model and Applied Social Science.” Advances in Neural Information Processing Systems Workshop on Topic Models: Computation, Application, and Evaluation.Google Scholar
Rost, Nicolas, Schneider, Gerald, and Kleibl, Johannes. 2009. “A Global Risk Assessment Model for Civil Wars.” Social Science Research 38 (4): 921–33.CrossRefGoogle Scholar
Sambanis, Nicholas. 2004. “What is Civil War? Conceptual and Empirical Complexities of an Operational Definition.” Journal of Conflict Resolution 48 (6): 814–58.Google Scholar
Schrodt, P. A., Gerner, D. J., and Yilmaz, O.. 2009. “Conflict and Mediation Event Observations (CAMEO): An Event Data Framework for a Post Cold War World.” In International Conflict Mediation: New Approaches and Findings, ed. Bercovitch, Jacob and Sigmund Gartner, Scott. New York: Routledge.Google Scholar
Schrodt, Philip A., Yonamine, James, and Bagozzi, Benjamin E.. 2013. “Data-Based Computational Approaches to Forecasting Political Violence.” In Handbook of Computational Approaches to Counterterrorism, ed V.S. Subrahmanian. New York: Springer, 129–62.CrossRefGoogle Scholar
Ward, Michael D., Greenhill, Brian D., and Bakke, Kristin M.. 2010. “The Perils of Policy by P-Value: Predicting Civil Conflicts.” Journal of Peace Research 47 (4): 363–75.Google Scholar
Ward, Michael D., Metternich, Nils W., Dorff, Cassy L., Gallop, Max, Hollenbach, Florian M., Schultz, Anna, and Weschle, Simon. 2013. “Learning from the Past and Stepping into the Future: Toward a New Generation of Conflict Prediction.” International Studies Review 15 (4): 473–90.Google Scholar
Weidmann, Nils B. 2016. “A Closer Look at Reporting Bias in Conflict Event Data.” American Journal of Political Science 60 (1): 206–18.Google Scholar
Woolley, John T. 2000. “Using Media-Based Data in Studies of Politics.” American Journal of Political Science 44 (1): 156–73.Google Scholar
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