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 …

Analyzing conflicts and political violence around the world is a persistent challenge in the
political science and policy communities due in large part to the vast volumes of specialized …

This article presents results and lessons learned from a prediction competition organized by
ViEWS to improve collective scientific knowledge on forecasting (de-) escalation in Africa …

As both satellite imagery and image-based machine learning methods continue to improve
and become more accessible, they are being utilized in an increasing number of sectors and …

Inspired by other fields, political scientists have embraced the use of supervised learning for
prediction, inference, measurement and description. In doing so, they typically use flexible …

Previous conflict forecasting efforts identified three areas for improvement: the importance of
spatiotemporal dependencies and nonlinearities and the further exploitation of latent …

Terrorists and other transnational extremist groups are responsible for thousands of civilian
deaths. In confronting extremists, governments have relied heavily on threats, demands …

This study advances the field of conflict forecasting by using text-based actor embeddings
with transformer models to predict dynamic changes in violent conflict patterns at the actor …

In the world of cyber defense, anticipating potential attacks or any increase in risk of attacks
is one of the most advantageous pieces of knowledge one can have. However, little …

Terrorism is complex, with a huge scope of belief systems, reasons, entertainers, and
objectives, and it represents a danger not exclusively to assemblies and organizations, yet …