• DocumentCode
    1661822
  • Title

    Discovering the Evolutionary Patterns in Local Topology of an E-Mail Social Network

  • Author

    Juszczyszyn, Krzysztof ; Frys, Wojciech

  • Author_Institution
    Inst. of Comput. Sci., Wroclaw Univ. of Technol., Wroclaw, Poland
  • Volume
    3
  • fYear
    2011
  • Firstpage
    102
  • Lastpage
    105
  • Abstract
    We present a new approach to the quantifying changes in an email social network illustrated by the data from the Enron dataset). The Triad Transition Matrix containing the probabilities of transitions between triads is defined, then we show how it can help to discover the dynamic patterns of network evolution. The compatibility of the TTM approach with the existing methods of characterizing the local topology (network motifs) is discussed as well.
  • Keywords
    data mining; electronic mail; probability; social networking (online); topology; TTM approach; dynamic pattern discovery; e-mail social network; evolutionary pattern; transition probability; triad transition matrix; Biology; Complex networks; Educational institutions; Electronic mail; Social network services; Topology; dynamic social networks; triad enumeration; triad transitions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Lyon
  • Print_ISBN
    978-1-4577-1373-6
  • Electronic_ISBN
    978-0-7695-4513-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2011.21
  • Filename
    6040816