articleOct 26, 2010Closed access

You are where you tweet

Texas A&M University

Indexed incrossref

Abstract

We propose and evaluate a probabilistic framework for estimating a Twitter user's city-level location based purely on the content of the user's tweets, even in the absence of any other geospatial cues. By augmenting the massive human-powered sensing capabilities of Twitter and related microblogging services with content-derived location information, this framework can overcome the sparsity of geo-enabled features in these services and enable new location-based personalized information services, the targeting of regional advertisements, and so on. Three of the key features of the proposed approach are: (i) its reliance purely on tweet content, meaning no need for user IP information, private login information,…

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1,080
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119.48
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100%
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Authors

3

Topics & keywords

Keywords
  • Geotagging
  • Computer science
  • Microblogging
  • Social media
  • Geospatial analysis
  • Probabilistic logic
  • Information retrieval
  • User-generated content
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