Recent research on the forecasting of violence has mostly focused on predicting the presence or absence of conflict in a given location, while much less attention has been paid to predicting changes in violence. We organized a prediction competition to forecast changes in state-based violence both for the true future and for a test partition. We received contributions from 15 international teams. The models leverage new insight on the targeted problem, insisting on methodological advances, new data and features, and innovative frameworks which contribute to the research frontiers from various perspectives. This article introduces the competition, presents the main innovations fostered by the teams and discusses ways to further expand and improve upon this wisdom of the crowd. We show that an optimal modeling approach builds on a good number of the presented contributions and new evaluation metrics are needed to capture substantial models’ improvements and reward unique insights.
Hegre, Håvard; Paola Vesco & Michael Colaresi (2022) Lessons from an escalation prediction competition, International Interactions 48 (4): 521–554.