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Online Social Network User Behavior Analysis — With RenRen Case

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Human Centered Computing (HCC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9567))

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Abstract

This paper investigated typical user behaviors in RenRen and used a clustering algorithm that assigns users to groups through a distance measure that is computed based on the values of user feature vector. The user feature vector consists of four attributes and we got six user groups from the clustering process. By analyzing the six different user behavior patterns, we considered some strategies for providers to improve their service quality.

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References

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Author information

Authors and Affiliations

  1. College of Management Science and Engineering, Shandong Normal University, Jinan, China

    Wenqian Wang & Yinghong Ma

Authors
  1. Wenqian Wang
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  2. Yinghong Ma
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Corresponding authors

Correspondence to Wenqian Wang or Yinghong Ma .

Editor information

Editors and Affiliations

  1. Wuhan, Hubei, China

    Qiaohong Zu

  2. Fujitsu Laboratories of Europe Ltd., Middlesex, United Kingdom

    Bo Hu

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© 2016 Springer International Publishing Switzerland

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Cite this paper

Wang, W., Ma, Y. (2016). Online Social Network User Behavior Analysis — With RenRen Case. In: Zu, Q., Hu, B. (eds) Human Centered Computing. HCC 2016. Lecture Notes in Computer Science(), vol 9567. Springer, Cham. https://doi.org/10.1007/978-3-319-31854-7_101

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  • DOI: https://doi.org/10.1007/978-3-319-31854-7_101

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31853-0

  • Online ISBN: 978-3-319-31854-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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