Forecasting Ukrainian Refugee Flows With Organic Data Sources

This paper explores the use of organic data to predict forced migration from Ukraine to five neighboring countries. The study combines Twitter conversations with event and fatality data from the Armed Conflict Location and Event Data Project (ACLED) and develops predictive models of forced displacement. The results suggest that Twitter variables were more important predictors in the first phase of the conflict, while event-based predictors were more important in the second phase.

Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration

Worldwide displacement due to war and conflict is at all-time high. Unfortunately, determining if, when, and where people will move is a complex problem. This paper proposes integrating both publicly available organic data from social media and …