Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles: The dynamics of the "location" field in user profiles

Brent Hecht, Lichan Hong, Bongwon Suh, Ed H. Chi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

284 Scopus citations

Abstract

Little research exists on one of the most common, oldest, and most utilized forms of online social geographic information: the "location" field found in most virtual community user profiles. We performed the first in-depth study of user behavior with regard to the location field in Twitter user profiles. We found that 34% of users did not provide real location information, frequently incorporating fake locations or sarcastic comments that can fool traditional geographic information tools. When users did input their location, they almost never specified it at a scale any more detailed than their city. In order to determine whether or not natural user behaviors have a real effect on the "locatability" of users, we performed a simple machine learning experiment to determine whether we can identify a user's location by only looking at what that user tweets. We found that a user's country and state can in fact be determined easily with decent accuracy, indicating that users implicitly reveal location information, with or without realizing it. Implications for location-based services and privacy are discussed.

Original languageEnglish (US)
Title of host publicationCHI 2011 - 29th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings and Extended Abstracts
Pages237-246
Number of pages10
DOIs
StatePublished - Jun 13 2011
Event29th Annual CHI Conference on Human Factors in Computing Systems, CHI 2011 - Vancouver, BC, Canada
Duration: May 7 2011May 12 2011

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other29th Annual CHI Conference on Human Factors in Computing Systems, CHI 2011
CountryCanada
CityVancouver, BC
Period5/7/115/12/11

Keywords

  • Geography
  • Location
  • Location prediction
  • Location-based services
  • Privacy
  • Social networks
  • Twitter

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