File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Measuring global migration flows using online data

TitleMeasuring global migration flows using online data
Authors
Keywordshuman migration
international migration
migration flow
Issue Date6-May-2025
PublisherNational Academy of Sciences
Citation
Proceedings of the National Academy of Sciences, 2025, v. 122, n. 18 How to Cite?
AbstractExisting estimates of human migration are limited in their scope, reliability, and timeliness, prompting the United Nations and the Global Compact on Migration to call for improved data collection. Using privacy protected records from three billion Facebook users, we estimate country-to-country migration flows at monthly granularity for 181 countries, accounting for selection into Facebook usage. Our estimates closely match high-quality measures of migration where available but can be produced nearly worldwide and with less delay than alternative methods. We estimate that 39.1 million people migrated internationally in 2022 (0.63% of the population of the countries in our sample). Migration flows significantly changed during the COVID-19 pandemic, decreasing by 64% before rebounding in 2022 to a pace 24% above the precrisis rate. We also find that migration from Ukraine increased tenfold in the wake of the Russian invasion. To support research and policy interventions, we release these estimates publicly through the Humanitarian Data Exchange.
Persistent Identifierhttp://hdl.handle.net/10722/358181
ISSN
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 3.737
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChi, Guanghua-
dc.contributor.authorAbel, Guy J.-
dc.contributor.authorJohnston, Drew-
dc.contributor.authorGiraudy, Eugenia-
dc.contributor.authorBailey, Mike-
dc.date.accessioned2025-07-25T00:30:35Z-
dc.date.available2025-07-25T00:30:35Z-
dc.date.issued2025-05-06-
dc.identifier.citationProceedings of the National Academy of Sciences, 2025, v. 122, n. 18-
dc.identifier.issn0027-8424-
dc.identifier.urihttp://hdl.handle.net/10722/358181-
dc.description.abstractExisting estimates of human migration are limited in their scope, reliability, and timeliness, prompting the United Nations and the Global Compact on Migration to call for improved data collection. Using privacy protected records from three billion Facebook users, we estimate country-to-country migration flows at monthly granularity for 181 countries, accounting for selection into Facebook usage. Our estimates closely match high-quality measures of migration where available but can be produced nearly worldwide and with less delay than alternative methods. We estimate that 39.1 million people migrated internationally in 2022 (0.63% of the population of the countries in our sample). Migration flows significantly changed during the COVID-19 pandemic, decreasing by 64% before rebounding in 2022 to a pace 24% above the precrisis rate. We also find that migration from Ukraine increased tenfold in the wake of the Russian invasion. To support research and policy interventions, we release these estimates publicly through the Humanitarian Data Exchange.-
dc.languageeng-
dc.publisherNational Academy of Sciences-
dc.relation.ispartofProceedings of the National Academy of Sciences-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjecthuman migration-
dc.subjectinternational migration-
dc.subjectmigration flow-
dc.titleMeasuring global migration flows using online data-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1073/pnas.2409418122-
dc.identifier.pmid40299700-
dc.identifier.scopuseid_2-s2.0-105004339198-
dc.identifier.volume122-
dc.identifier.issue18-
dc.identifier.eissn1091-6490-
dc.identifier.isiWOS:001485491000001-
dc.identifier.issnl0027-8424-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats