Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Friendship Influence on Mobile Behavior of Location Based Social Network Users

  • Song, Yang (State Key Laboratory of Networking and Switching Technology, Beijing University) ;
  • Hu, Zheng (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Institute of Sensing Technology and Business, BUPT) ;
  • Leng, Xiaoming (State Key Laboratory of Networking and Switching Technology, Beijing University) ;
  • Tian, Hui (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications) ;
  • Yang, Kun (School of Computer Science and Electronic Engineering (CSEE), University of Essex) ;
  • Ke, Xin (China Telecom Corporation Limited Beijing Research Institute)
  • Received : 2014.08.30
  • Published : 2015.04.30
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Abstract

In mobile computing research area, it is highly desirable to understand the characteristics of user movement so that the user friendly location aware services could be rendered effectively. Location based social networks (LBSNs) have flourished recently and are of great potential for movement behavior exploration and datadriven application design. While there have been some efforts on user check-in movement behavior in LBSNs, they lack comprehensive analysis of social influence on them. To this end, the social-spatial influence and social-temporal influence are analyzed synthetically in this paper based on the related information exposed in LBSNs. The check-in movement behaviors of users are found to be affected by their social friendships both from spatial and temporal dimensions. Furthermore, a probabilistic model of user mobile behavior is proposed, incorporating the comprehensive social influence model with extent personal preference model. The experimental results validate that our proposed model can improve prediction accuracy compared to the state-of-the-art social historical model considering temporal information (SHM+T), which mainly studies the temporal cyclic patterns and uses them to model user mobility, while being with affordable complexity.

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References

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