Framework to Study Migration Decisions Using Call Detail Record (CDR) Data

Viren Dias, Lasantha Fernando, Yusen Lin, Vanessa Frías-Martínez, Louiqa Raschid

Abstract: This article addresses the challenges of using call detail record (CDR) data to study migration. Repurposing CDR data for this task have many advantages, including the lower costs of data collection and the potential for contemporaneous analysis. We present a framework for the repurposing and analysis of CDR data. We identify the home location of a subscriber, with corresponding confidence measures, and determine if the subscriber is a definite migrant, likely migrant, likely nonmigrant, or definite nonmigrant. A predictive model then uses mobility and social network features, extracted from the CDR data, to predict the individual decision to migrate. We are the first to address the challenging task of predicting the migration decision at the individual level. We also provide insight into features that can have an impact on the decision to migrate. An in-depth evaluation using CDR data from two provinces in Sri Lanka provides a granular map of migrant inflow and outflow. The success of our prediction model and the insights gained from the evaluation prepare the way for the repurposing of CDR data for social good with a focus on migration.