Malmö University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Can internet search data predict human migration intentions?
Malmö University, Faculty of Culture and Society (KS), Department of Global Political Studies (GPS).ORCID iD: 0000-0003-0268-1471
City University of New York, New York, NY, USA.ORCID iD: 0000-0002-8811-3856
Malmö University, Faculty of Culture and Society (KS), Department of Global Political Studies (GPS).ORCID iD: 0000-0002-7001-4526
2025 (English)In: Comparative Migration Studies, ISSN 2214-8590, E-ISSN 2214-594X, Vol. 13, no 1, article id 28Article in journal (Refereed) Published
Abstract [en]

Internet search data may reveal people’s intentions to migrate, as aspiring migrants tend to use online search engines to explore migration opportunities. However, unlike official migration statistics, search data may only reflect the behavior of a self-selected subset of the population, raising concerns about its generalizability. This article integrates traditional survey data - Gallup World Poll (GWP) - with Google Trends, search engine market share, and internet adoption rate to examine the extent to which search trends of migration-related topics can serve as proxies for migration intentions. The results reveal that, on a global scale, passport-related search queries strongly correlate with individuals’ intentions to migrate. However, at the country level, particularly in the global south, migration intentions are more accurately predicted by the adoption rates of Google search rather than search topics per se. These findings underscore the importance of detecting and correcting user selection biases when leveraging digital trace data for migration research, ensuring robust and representative insights into the spatial-temporal patterns of human mobility.

Place, publisher, year, edition, pages
Springer Nature , 2025. Vol. 13, no 1, article id 28
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mau:diva-76105DOI: 10.1186/s40878-025-00450-2ISI: 001485048600001Scopus ID: 2-s2.0-105004457001OAI: oai:DiVA.org:mau-76105DiVA, id: diva2:1961417
Available from: 2025-05-27 Created: 2025-05-27 Last updated: 2025-05-28Bibliographically approved

Open Access in DiVA

fulltext(6282 kB)59 downloads
File information
File name FULLTEXT01.pdfFile size 6282 kBChecksum SHA-512
34902800c9140ca25b14df2dd07b8849da9a5a6a92c17646e6a3b1f0c1420095654805dfe842298804a99c50f1f9da70b1b37b9c00334bb1a6584e53c50bd907
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Qi, HaodongBevelander, Pieter

Search in DiVA

By author/editor
Qi, HaodongReed, Holly E.Bevelander, Pieter
By organisation
Department of Global Political Studies (GPS)
In the same journal
Comparative Migration Studies
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 59 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 202 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf