• DocumentCode
    653277
  • Title

    On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity

  • Author

    Kibanov, Mark ; Atzmueller, Martin ; Scholz, Christoph ; Stumme, Gerd

  • Author_Institution
    Knowledge & Data Eng. Group, Univ. of Kassel, Kassel, Germany
  • fYear
    2013
  • fDate
    20-23 Aug. 2013
  • Firstpage
    993
  • Lastpage
    1000
  • Abstract
    Communities are a central aspect in the formation of social interaction networks. In this paper, we analyze the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific conferences. We compare the basic properties of the contact graphs to describe the properties of the contact networks and analyze the resulting community structure using state-of-the-art automic community detection algorithms. Specifically, we analyze the evolution of contacts and communities over time to consider the stability of the respective communities. In addition, we assess different factors which have an influence on the quality of community prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.
  • Keywords
    data mining; graph theory; graphs; social aspects of automation; automic community detection algorithms; community prediction; face to face contact networks; face to face proximity; social interaction networks; stability; Clustering algorithms; Communities; Conferences; Context; Detection algorithms; Image edge detection; Stability analysis; communities; social networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/GreenCom-iThings-CPSCom.2013.170
  • Filename
    6682184