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Evolution Analysis of a Mobile Social Network

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Book cover Advanced Data Mining and Applications (ADMA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6440))

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Abstract

Smart phones and ubiquitous wireless connections are helping people to build and maintain mobile social relationships. We present an in-depth and complete evolution analysis on the user activities and social graph of a mobile social network using data obtained from Nokia Friend View. Our results show that (1) user activities in Friend View are highly correlated and the power law fitted exponents for user activities distribution are slowly becoming larger over time, which appears to be contrary to the famous “rich get richer” assertion in the preferential attachment model because users in Friend View regard the reciprocity as important during the interaction and (2) both undirected friend network and directed comment network in Friend View are small-world and scale-free networks over time with slowly decreasing clustering coefficient. However, compared to online social networks where users have a large number of friends but loose weakly-tied subgroups, users in Friend View tend to have close strongly-tied cohesive subgroups. The results can help us understand users’ social activities and interactions over time in mobile social networks.

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Author information

Authors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Hao Wang

  2. Nokia Research Center, Beijing, 100176, China

    Hao Wang & Alvin Chin

Authors
  1. Hao Wang
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  2. Alvin Chin
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, University of Technology Sydney, 2007, Sydney, NSW, Australia

    Longbing Cao

  2. College of Computer Science, Chongqing University, 400030, Chongqing, China

    Yong Feng

  3. College of Computer Science, Chongqing University , 400030, Chongqing, China

    Jiang Zhong

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Wang, H., Chin, A. (2010). Evolution Analysis of a Mobile Social Network. In: Cao, L., Feng, Y., Zhong, J. (eds) Advanced Data Mining and Applications. ADMA 2010. Lecture Notes in Computer Science(), vol 6440. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17316-5_31

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  • DOI: https://doi.org/10.1007/978-3-642-17316-5_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17315-8

  • Online ISBN: 978-3-642-17316-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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