Identifying Meaningful Indirect Indicators of Migration for Different Conflicts

TL;DR

This paper proposes a methodology combining behavioral, event, and traditional data sources to predict migration during conflicts, demonstrated through a case study in Iraq and extended to Venezuela.

Contribution

It introduces a novel approach for identifying indirect indicators of migration using diverse data sources during conflict situations.

Findings

Successful prediction of mass movement in Iraq (2015-2017)

Extension of methodology to Venezuela

Potential for real-time migration monitoring

Abstract

This extended abstract describes an ongoing project that attempts to blend publicly available organic, real time behavioral data, event data, and traditional migration data to determine when and where people will move during times of instability. We present a methodology that was successful for a case study predicting mass movement in Iraq from 2015 - 2017, and discuss how we are extending it to capture indirect indicators of movement in Venezuela.