ViEWS: A political violence early-warning system
| Autor: | Hegre, Håvard, Allansson, Marie, Basedau, Matthias, Colaresi, Michael, Croicu, Mihai, Fjelde, Hanne, Hoyles, Frederick, Hultman, Lisa, Högbladh, Stina, Jansen, Remco, Mouhleb, Naima, Muhammad, Sayyed Auwn, Nilsson, Desirée, Nygård, Håvard Mokleiv, Olafsdottir, Gudlaug, Petrova, Kristina, Randahl, David, Rød, Espen Geelmuyden, Schneider, Gerald, Uexkull, Nina von, Vestby, Jonas |
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| Rok vydání: | 2019 |
| Předmět: |
Politikwissenschaft
Political science Friedens- und Konfliktforschung Sicherheitspolitik Peace and Conflict Research International Conflicts Security Policy innere Sicherheit politischer Konflikt internationaler Konflikt Konfliktpotential Konfliktbewältigung Konfliktlösung Konfliktforschung Prävention Frühwarnsystem Afrika domestic security political conflict international conflict conflict potential conflict mediation conflict resolution conflict research prevention early warning system Africa 10500 |
| Zdroj: | Journal of Peace Research, 56, 2, 155-174 |
| Druh dokumentu: | Zeitschriftenartikel<br />journal article<br />article |
| ISSN: | 1460-3578 |
| DOI: | 10.1177/0022343319823860 |
| Popis: | This article presents ViEWS - a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnational level for 36 months into the future and all three UCDP types of organized violence: state-based conflict, non-state conflict, and one-sided violence in Africa. The article presents the methodology and data behind these forecasts, evaluates their predictive performance, provides selected forecasts for October 2018 through October 2021, and indicates future extensions. ViEWS is built as an ensemble of constituent models designed to optimize its predictions. Each of these represents a theme that the conflict research literature suggests is relevant, or implements a specific statistical/machine-learning approach. Current forecasts indicate a persistence of conflict in regions in Africa with a recent history of political violence but also alert to new conflicts such as in Southern Cameroon and Northern Mozambique. The subsequent evaluation additionally shows that ViEWS is able to accurately capture the long-term behavior of established political violence, as well as diffusion processes such as the spread of violence in Cameroon. The performance demonstrated here indicates that ViEWS can be a useful complement to non-public conflict-warning systems, and also serves as a reference against which future improvements can be evaluated. |
| Databáze: | SSOAR – Social Science Open Access Repository |
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