• DocumentCode
    2835669
  • Title

    Clustering Users in Micro Blogging Social Networks Using Probabilistic Topic Modeling - A Framework

  • Author

    Dolatabadi, Hossein ; Soon, Lay-Ki ; Shirazi, Mahdi Negahi ; Mohammadi, Mohammad

  • Author_Institution
    Fac. of Comput. & Inf., Multimedia Univ., Selangor, Malaysia
  • fYear
    2012
  • fDate
    18-21 June 2012
  • Firstpage
    113
  • Lastpage
    116
  • Abstract
    Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks´ users creates the necessity of extracting and analyzing the contents of the users´ notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.
  • Keywords
    Internet; mobile computing; pattern clustering; probability; social networking (online); text analysis; World Wide Web; microblogging social network; mobile technology; multimedia product; probabilistic topic modeling; user clustering; Algorithm design and analysis; Blogs; Clustering algorithms; Data mining; Media; Twitter; Latent Dirichlet Allocation (LDA); Micro blogging; Social network; Topic modeling algorithm; User clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Its Applications (ICCSA), 2012 12th International Conference on
  • Conference_Location
    Salvador
  • Print_ISBN
    978-1-4673-1691-0
  • Type

    conf

  • DOI
    10.1109/ICCSA.2012.28
  • Filename
    6257619