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Conflict Forecasting

Conflict forecasting is the enterprise of producing calibrated, regularly updated probabilistic predictions of where and when armed conflict will occur, to support early warning and prevention. Exemplified by operational systems such as ViEWS (Hegre et al. 2019), it combines historical conflict data and predictors at fine spatial and temporal resolution, fits and ensembles multiple models, and forecasts violence months ahead — then rigorously evaluates those forecasts against what actually happens. It differs from explanatory conflict analysis by being transparent, prospective, and judged on out-of-sample accuracy rather than on coefficients.

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Conflict Forecasting and Political Violence Early Warning

Catatan metode taksonomi · ml-model / international-relations

Hegre, H., Allansson, M., Basedau, M., Colaresi, M., Croicu, M., Fjelde, H., et al. (2019). ViEWS: A political violence early-warning system. Journal of Peace Research, 56(2), 155–174. · DOI 10.1177/0022343319823860

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Same method familyMachine Learning Conflict Predictionmachine-suggested · Relational suggestion, not evidence.Used in the same domainSpatial Conflict Analysismachine-suggested · Relational suggestion, not evidence.Used in the same domainUCDP Conflict Data Analysismachine-suggested · Relational suggestion, not evidence.