Personal and Ubiquitous Computing

, Volume 17, Issue 4, pp 605–620 | Cite as

Urban area characterization based on crowd behavioral lifelogs over Twitter

  • Ryong LeeEmail author
  • Shoko Wakamiya
  • Kazutoshi Sumiya
Original Article


Recent location-based social networking sites are attractively providing us with a novel capability of monitoring massive crowd lifelogs in the real-world space. In particular, they make it easier to collect publicly shared crowd lifelogs in a large scale of geographic area reflecting the crowd’s daily lives and even more characterizing urban space through what they have in minds and how they behave in the space. In this paper, we challenge to analyze urban characteristics in terms of crowd behavior by utilizing crowd lifelogs in urban area over the social networking sites. In order to collect crowd behavioral data, we exploit the most famous microblogging site, Twitter, where a great deal of geo-tagged micro lifelogs emitted by massive crowds can be easily acquired. We first present a model to deal with crowds’ behavioral logs on the social network sites as a representing feature of urban space’s characteristics, which will be used to conduct crowd-based urban characterization. Based on this crowd behavioral feature, we will extract significant crowd behavioral patterns in a period of time. In the experiment, we conducted the urban characterization by extracting the crowd behavioral patterns and examined the relation between the regions of common crowd activity patterns and the major categories of local facilities.


Urban characteristics Crowd behavior Location-based social network sites Microblogs 



This research was supported in part by the 7th Microsoft Research IJARC Core Project.


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Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  1. 1.University of HyogoHimejiJapan
  2. 2.National Institute of Information and Communications Technology (NICT)KyotoJapan

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