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Research Article

Crystal Cube: Forecasting Disruptive Events

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Article: 2001179 | Received 18 Aug 2021, Accepted 28 Oct 2021, Published online: 12 Nov 2021

References

  • Arva, B., J. Beieler, B. Fischer, G. Lara, P. A. Schrodt, W. Song, M. Sowell, and S. Stehle. 2013. Improving forecasts of international events of interest. EPSA.
  • Beger, A., C. L. Dorff, and D. Ward. 2016. Irregular leadership changes in 2014: Forecasts using ensemble, split-population duration models. International Journal of Forecasting 32 (1):258–281. doi:10.1016/j.ijforecast.2015.01.009.
  • Bell, C. 2016. The rulers, elections, and irregular governance dataset (REIGN). Accessed 2016. https://oefdatascience.github.io/REIGN.github.io.
  • Brandt, P., M. Colaresi, and J. R. Freeman. 2008. The dynamics of reciprocity, accountability, and credibility. Journal of Conflict Resolution (Department of Defense) 52 (3):343–74. doi:10.1177/0022002708314221.
  • Bueno de Mesquita, B. 1980. An expected utility theory of international conflict. American Political Science Review 74 (4):917–31. doi:10.2307/1954313.
  • Bueno de Mesquita, B. 1983. The war trap. New Haven, CT: Yale University Press.
  • Bueno de Mesquita, B. 1984. Forecasting policy decisions: An expected utility approach to post-Khomeini Iran. PS, Political Science & Politics 17 (2):226–36. doi:10.2307/418786.
  • Della Porta, D. 1995. Social movements, political violence, and the state: A comparative analysis of Italy and Germany. Cambridge: Cambridge University Press.
  • Della Porta, D. 2013. Meeting democracy: Power and deliberation in global justice movements. Cambridge: Cambridge University Press.
  • Department of Defense. 2005. US national defense strategy. Washington.
  • Diermeier, D., and T. Feddersen. 1998. Cohesion in legislatures and the vote of confidence procedure. American Political Science Review 92 (3):611–21. doi:10.2307/2585484.
  • Eckstein, S., ed. 1989. Power and popular protest: Latin American social movements. Berkeley: University of California Press.
  • Fritsch, F. N., and R. E. Carlson. 1980. Monotone piecewise cubic interpolation. SIAM Journal on Numerical Analysis 17 (2):238–46. doi:10.1137/0717021.
  • Goemans, H. E., K. S. Gleditsch, and G. Chiozza. 2009. Introducing ARCHIGOS: A dataset of political leaders. Journal of Peace Research 46 (2):269–83. doi:10.1177/0022343308100719.
  • Gurr, T. R. 1970. Why men rebel. Princeton, NJ: Princeton University Press.
  • Hegre, H., H. Buhaug, K. V. Calvin, J. Nordkvelle, S. T. Waldhoff, and E. Gilmore. 2016. Forecasting civil conflict along the shared socioeconomic pathways. Environmental Research Letters 11 (5):054002. doi:10.1088/1748-9326/11/5/054002.
  • Hegre, H., J. Karlsen, H. M. Nygård, H. Strand, and H. Urdal. 2013. Predicting Armed Conflict, 2010-2050. International Studies Quarterly 57 (2):250–70. doi:10.1111/isqu.12007.
  • Hegre, H., M. Allanssona, M. Basedaua, M. Colaresia, M. Croicua, H. Fjeldea, F. Hoylesa, L. Hultman, S. Högbladh, R. Jansen, et al. 2019. ViEWS: A political violence early-warning system. Journal of Peace Research. 56 (2):155–74. doi:10.1177/0022343319823860.
  • Hegre, H., N. W. Metternich, H. Mokleiv, and J. Wucherpfennig. 2017. Introduction: Forecasting in peace research. Journal of Peace Research 54 (2):113–24. doi:10.1177/0022343317691330.
  • Herb, M. 1999. All in the family: Absolutism, revolution, and democracy in the Middle Eastern Monarchies. Albany: State University of New York Press.
  • Hinton, G. E., and R. Salakhutdinov. 2006. Reducing the dimensionality of data with neural networks. Science 313 (5786):504–07. doi:10.1126/science.1127647.
  • Hochreiter, S., and J. Schmidhuber. 1997. Long short-term memory. Neural Computation 9 (8):1735–80. doi:10.1162/neco.1997.9.8.1735.
  • Lafferty, J., A. McCallum, and F. C. N. Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. International Conference on Machine Learning, Williams College, June 28 - July 1, 2001.
  • Laver, M., and N. Schofield. 1990. Multiparty government: The politics of coalition in Europe. Oxford: Oxford University Press.
  • Leetaru, K. H. 2017. Global database of events, language and tone 1.0. https://www.gdeltproject.org
  • Lundberg, S. M., and S.-I. Lee. 2017. A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems 30 (NIPS 2017).
  • Lustick, I., S. O’Brien, S. Shellman, T. Siedlecki, and M. Ward. 2015. ICEWS events of interest ground truth data set. https://dataverse.harvard.edu/dataverse/icews
  • McAdam, D. L. 1982. Political process and the development of black insurgency, 1930-1970. Chicago, IL: University of Chicago Press.
  • Montgomery, J. M., F. M. Hollenbach, and M. D. Ward. 2012. Improving predictions using ensemble Bayesian model averaging. Political Analysis 20 (3):271–91. doi:10.1093/pan/mps002.
  • Muthiah, S., P. Butler, R. P. Khandpur, P. Saraf, and N. Self. 2016. EMBERS at 4 years: Experiences operating an open source indicators forecasting system. 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA. August 13-17, 2016.
  • Parrish, N. H., A. L. Buczak, J. T. Zook, J. P. Howard, B. J. Ellison, and B. D. Baugher. 2018. Crystal cube: Multidisciplinary approach to disruptive events prediction. International Conference on Applied Human Factors and Ergonomics 571–81.
  • Perez-Linan, A. 2007. Presidential impeachment and the new political instability in Latin America. New York, NY: Cambridge University Press.
  • Qiao, F., P. Li, X. Zhang, Z. Ding, J. Cheng, and H. Wang. 2017. Predicting social unrest events with hidden Markov models using GDELT. Discrete Dynamics in Nature and Society 2017:1–13. doi:10.1155/2017/8180272.
  • Schrodt, P. A. 2012. CAMEO conflict and mediation event observations event and actor codebook. Pennsylvania State University, Event Data Project, University Park, PA.
  • Schrodt, P.A. 1988. Artificial intelligence and formal models of international behavior. Am Soc 19, 71–85. https://doi.org/10.1007/BF02692375
  • Schrodt, Philip A., 1991. “Prediction of Interstate Conflict Outcomes Using a Neural Network”, Social Science Computer Review 9:3.
  • Stevens, J. 2012. “Political scientists are lousy forecasters.” New York Times, June 23.
  • Thomson, R., T. Royed, E. Naurin, J. Artes, R. Costello, L. Ennser-Jedenastik, K. Praprotnik, P. Kostadinova, C. Moury, and F. Pétry. 2017. The fulfillment of parties’ election pledges: A comparative study on the impact of power sharing. American Journal of Political Science 61 (3):527–42. doi:10.1111/ajps.12313.
  • Tilly, C. 2002. Stories, identities, and political change. Lanham, MD: Rowman & Littlefield Publishers.
  • World Development Indicators. 2016. https:/data.worldbank.org/data-catalog/world-development-indicators
  • World Governance Indicators. 2016. https://data.worldbank.org/data-catalog/worldwide-governance-indicators