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A survey of location inference techniques on Twitter

Ajao, Oluwaseun; Hong, Jun; Liu, Weiru


Oluwaseun Ajao

Jun Hong
Professor in Artificial Intelligence

Weiru Liu


© The Author(s) 2015. The increasing popularity of the social networking service, Twitter, has made it more involved in day-to-day communications, strengthening social relationships and information dissemination. Conversations on Twitter are now being explored as indicators within early warning systems to alert of imminent natural disasters such as earthquakes and aid prompt emergency responses to crime. Producers are privileged to have limitless access to market perception from consumer comments on social media and microblogs. Targeted advertising can be made more effective based on user profile information such as demography, interests and location. While these applications have proven beneficial, the ability to effectively infer the location of Twitter users has even more immense value. However, accurately identifying where a message originated from or an author's location remains a challenge, thus essentially driving research in that regard. In this paper, we survey a range of techniques applied to infer the location of Twitter users from inception to state of the art. We find significant improvements over time in the granularity levels and better accuracy with results driven by refinements to algorithms and inclusion of more spatial features.


Ajao, O., Hong, J., & Liu, W. (2015). A survey of location inference techniques on Twitter. Journal of Information Science, 41(6), 855-864.

Journal Article Type Review
Acceptance Date Nov 20, 2015
Publication Date Jan 1, 2015
Deposit Date Feb 15, 2017
Journal Journal of Information Science
Print ISSN 0165-5515
Electronic ISSN 1741-6485
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 41
Issue 6
Pages 855-864
Keywords location inference, Twitter analytics, information retrieval
Public URL
Publisher URL