• DocumentCode
    531481
  • Title

    Empirical Analysis and Multiple Level Views in Massive Social Networks

  • Author

    Ye, Qi ; Wu, Bin ; Gao, Yuan ; Wang, Bai

  • Author_Institution
    Sch. of Comput. Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 3 2010
  • Firstpage
    541
  • Lastpage
    544
  • Abstract
    With the emergence of massive social media, massive social networks have led to a huge interest in data analysis. In this paper, we propose an empirical study on several massive social networks including 4 mobile call graphs, a fixed-line call graph, two co-authorship networks and two Email networks. We find that call graphs tend to be more locality than the co-authorship networks and Email networks. To our surprise, we even find that there is no significant relations between community sizes and their quality scores for most extracted communities. We also find that some very huge community with high mean quality values, and we can not find the universal "V" shape in their mean quality values.
  • Keywords
    data analysis; graph theory; information networks; social networking (online); coauthorship network; data analysis; email network; empirical analysis; fixed line call graph; massive social media; massive social network; mean quality value; mobile call graph; multiple level view; universal V shape; Call graphs; Community; Graph Mining; Social Network Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-8482-9
  • Electronic_ISBN
    978-0-7695-4191-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2010.48
  • Filename
    5616338