A survey of location inference techniques on Twitter

Oluwaseun Ajao, Jun Hong, Weiru Liu

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)
532 Downloads (Pure)


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 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 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.
Original languageEnglish
Pages (from-to)855-864
JournalJournal of Information Science
Issue number6
Publication statusPublished - Dec 2015


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