• DocumentCode
    3281483
  • Title

    Harnessing Wisdom of the Crowds Dynamics for Time-Dependent Reputation and Ranking

  • Author

    Daly, Elizabeth M.

  • Author_Institution
    IBM Software Group, Dublin Software Lab., Dublin, Ireland
  • fYear
    2009
  • fDate
    20-22 July 2009
  • Firstpage
    267
  • Lastpage
    272
  • Abstract
    The ldquowisdom of the crowdsrdquo is a concept used to describe the utility of harnessing group behaviour, where user opinion evolves over time and the opinion of the masses collectively demonstrates wisdom. Web 2.0 is a new medium where users are not just consumers, but are also contributors. By contributing content to the system, users become part of the network and relationships between users and content can be derived. Example applications are collaborative bookmarking networks such as delicious and file sharing applications such as YouTube and Flickr. These networks rely on user contributed content, described and classified using tags. The wealth of user generated content can be hard to navigate and search due to difficulties in comparing documents with similar tags and the application of traditional information retrieval scoring techniques are limited. Evaluating the time evolving interests of users may be used to derive quality of content. In this paper, we propose a technique to rank documents based on reputation. The reputation is a combination of the number of bookmarkers, the reputation of the bookmarking user and the time dynamics of the document. Experimental results and analysis are presented on a large collaborative IBM bookmarking network called Dogear.
  • Keywords
    Internet; behavioural sciences computing; document handling; information retrieval; social networking (online); Dogear; Web 2.0; bookmarking user; document ranking; group behaviour; information retrieval; large collaborative IBM bookmarking network; time-dependent reputation; user generated content; user opinion; wisdom-of-the crowds dynamics; Collaboration; Information retrieval; Navigation; Peer to peer computing; Search engines; Social network services; Tagging; User-generated content; Web pages; YouTube; Ranking; Reputation; Social Search; Social bookmarking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
  • Conference_Location
    Athens
  • Print_ISBN
    978-0-7695-3689-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2009.69
  • Filename
    5231866