• DocumentCode
    2897819
  • Title

    Digging Digg: Comment Mining, Popularity Prediction, and Social Network Analysis

  • Author

    Jamali, Salman ; Rangwala, Huzefa

  • Author_Institution
    Dept. of Comput. Sci. & Eng., George Mason Univ., Fairfax, VA, USA
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    32
  • Lastpage
    38
  • Abstract
    Using comment information available from Digg we define a co-participation network between users. We focus on the analysis of this implicit network, and study the behavioral characteristics of users. Using an entropy measure, we infer that users at Digg are not highly focused and participate across a wide range of topics. We also use the comment data and social network derived features to predict the popularity of online content linked at Digg using a classification and regression framework. We show promising results for predicting the popularity scores even after limiting our feature extraction to the first few hours of comment activity that follows a Digg submission.
  • Keywords
    data mining; entropy; feature extraction; pattern classification; regression analysis; social networking (online); Digg; behavioral characteristics; classification framework; comment mining; coparticipation network; entropy measure; feature extraction; implicit network analysis; popularity prediction; regression framework; social network analysis; Collaborative work; Computer science; Discussion forums; Entropy; Information analysis; Information systems; Particle measurements; Pattern analysis; Social network services; Yarn; Comment Mining; Egonet Analysis; Popularity Prediction; Social Bookmarking; Social Network Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems and Mining, 2009. WISM 2009. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3817-4
  • Type

    conf

  • DOI
    10.1109/WISM.2009.15
  • Filename
    5368318