Following Human Mobility Using Tweets

  • Mahdi Azmandian
  • Karan Singh
  • Ben Gelsey
  • Yu-Han Chang
  • Rajiv Maheswaran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7607)


The availability of location-based agent data is growing rapidly, enabling new research into the behavior patterns of such agents in space and time. Previously, such analysis was limited to either small experiments with GPS-equipped agents, or proprietary datasets of human cell phone users that cannot be disseminated across the academic community for followup studies. In this paper, we study the movement patterns of Twitter users in London, Los Angeles, and Tokyo. We cluster these agents by their movement patterns across space and time. We also show that it is possible to infer part of the underlying transportation net- work from Tweets alone, and uncover interesting differences between the behaviors exhibited by users across these three cities.


Human Mobility Twitter User Broad Geographic Area Move Object Database Cell Phone User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mahdi Azmandian
    • 1
  • Karan Singh
    • 1
  • Ben Gelsey
    • 1
  • Yu-Han Chang
    • 1
  • Rajiv Maheswaran
    • 1
  1. 1.Information Sciences InstituteUniversity of Southern CaliforniaMarina del ReyUSA

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