Predicting the escalation of conflict: A global forecasting approach to conflict escalation using big data
The key objective of this research project is to forecast conflict escalation of intra-state conflicts. In the past few years an increasing number of researchers are becoming interested in forecasting conflicts. This goes along with a more general interest in political science forecasting of elections, regime transitions, and terrorism.
Methodological, technological, and data-related (big data) advances are making it possible to forecast one of the most complicated phenomena: social behavior. Existing forecast models of conflict have very much focused on the occurrence of conflict but not their intensity. However, forecasting the intensity of conflicts is important to implement adequate policy responses, build resilience, and prepare early action. Especially, in the context of limited resources, when reacting to conflict around the world it is not only important to know if conflict occurs, but when and where it escalates.
This research projects develops split-population forecasting models that predict both, the occurence and escalation of conflict. The research has clearly impact oriented strategy by delivering software packages, web-based prediction tools, and implementation strategies for government, non-government, and corporate users.