Office of the Senior Vice President for Research
Office of the Senior Vice President for Research

Forced Migration

Predicting and Preventing Displacement at Scale

Millions of people are displaced every year due to conflict, famine, political instability, and climate-related disasters. Early warning systems can help governments and humanitarian organizations prepare for—and potentially prevent—mass displacement.

Georgetown researchers are developing a large-scale, data-intensive early warning system to detect potential forced migration events. Funded by the National Science Foundation, this pilot project brings together computer scientists, social scientists, and humanitarian experts to build predictive models that inform timely, life-saving interventions.

Our system analyzes global open-source media—including more than 600 million articles from the EOS database (formerly Raptor)—as well as social media and field-based interviews with displaced populations. By mining this data for triggers (such as violence or food insecurity) and trends (like worsening drought conditions), we generate insights that help aid agencies anticipate movement, position resources, and support both refugees and host communities.

A Collaborative Approach

Effective early warning systems depend on collaboration between those who understand the human factors behind displacement and those with the technical tools to analyze data at scale. Our project convenes researchers and practitioners from a variety of institutions and organizations. 

Project Partners

Principal Investigators

This interdisciplinary model fosters shared learning between social and computer scientists—advancing both fields and enhancing the real-world relevance of our research.

Project Outcomes

Acknowledgment

This work is supported by the National Science Foundation under Grant No. 1338507. The findings and views expressed are those of the authors and do not necessarily reflect those of the NSF.