Journal
JOURNAL OF INFORMATION SCIENCE
Volume 41, Issue 6, Pages 855-864Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0165551515602847
Keywords
Information retrieval; location inference; Twitter analytics
Funding
- EPSRC [EP/K004379/1, EP/H049606/1, EP/J006238/1, EP/G034303/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K004379/1, EP/G034303/1, EP/J006238/1, EP/H049606/1] Funding Source: researchfish
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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.
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