A new study co-authored by Professor Guy Abel of the Department of Sociology, Faculty of Social Sciences of the University of Hong Kong, alongside researchers from Meta and Harvard University, introduces a groundbreaking approach to measuring international migration. Published in the prestigious journal Proceedings of the National Academy of Sciences ( PNAS ), the research leverages online data to provide the most comprehensive and timely estimates of global migration flows to date.
The study, titled " Measuring Global Migration Flows Using Online Data ," was conducted by Professor Abel in collaboration with Meta researchers Guanghua Chi, Eugenia Giraudy, and Mike Bailey, as well as Drew Johnston from Harvard University. Their innovative approach utilises privacy-protected records from over three billion Facebook users to estimate monthly migration flows between 181 countries, accounting for biases in social media usage to generate reliable and near-real-time insights.
Key findings from the research include:
"This work addresses a critical gap in global migration data," said Professor Abel. "Past efforts pieced together various migration and demographic data to provide a tentative glimpse of global migration patterns. This new research takes a more direct approach, leveraging billions of anonymised digital traces to directly estimate when and where people migrate across borders. The estimates provide timely and detailed insights that can guide researchers, policymakers, and humanitarian efforts worldwide."
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Department of Sociology, Faculty of Social Sciences, HKU by email ( socidept@hku.hk )
Proceedings of the National Academy of Sciences
Observational study
Not applicable
Measuring global migration flows using online data
29-Apr-2025