A Study of Users’ Movements Based on Check-In Data in Location-Based Social Networks

  • Jinzhou Cao
  • Qingwu Hu
  • Qingquan Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8470)


With the development of GPS technology and the increasing popularity of mobile device, Location-based Social Networks (LBSN) has become a platform that promote the understanding of user behavior, which offers unique conditions for the study of users’ movement patterns.

Characteristics of users’ movements can be expressed by places they’ve visited. This paper presents a method to analyze characteristics of users’ movements in spatial and temporal domain based on data collected from a Chinese LBSN Sina Weibo. This paper analyzes spatial characteristics of users’ movement by clustering geographic areas through their check-in popularity. Meanwhile, temporal characteristics and variation of users’ movements on the timeline is analyzed by applying statistical method.


Spectral Cluster Mobile Social Networking Scenic Spot Spectral Cluster Algorithm Area Division 
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 2014

Authors and Affiliations

  • Jinzhou Cao
    • 1
  • Qingwu Hu
    • 1
  • Qingquan Li
    • 2
    • 3
  1. 1.School of Remote Sensing and Information EngineeringWuhan UniversityWuhanP.R. China
  2. 2.Shenzhen Key Laboratory of Spatial Smart Sensing and ServicesShenzhen UniversityShenzhenP.R. China
  3. 3.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanP.R. China

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