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A framework to restrict viewing of peer commentary on Web objects based on trust modeling

  • J. ChampaignEmail author
  • R. Cohen
  • N. Sardana
  • J. A. Doucette
Original Article

Abstract

In this paper, we present a framework aimed at assisting users in coping with the deluge of information within social networks. We focus on the scenario where a user is trying to digest feedback provided on a Web document (or a video) by peers. In this context, it is ideal for the user to be presented with a restricted view of all the commentary, namely those messages that are most beneficial in increasing the user’s understanding of the document. Operating within the computer science subfield of artificial intelligence, the centerpiece of our approach is a modeling of the trustworthiness of the person leaving commentary (the annotator), determined on the basis of ratings provided by peers, adjusted by a modeling of the similarity of those peers to the current user. We compare three competing formulae for restricting what is shown to users which vary in the extent to which they integrate trust modeling, to emphasize the value of this component. By simulating the knowledge gains achieved by users (inspired by methods used in peer-based intelligent tutoring), we are able to validate the effectiveness of our algorithms. Overall, we offer a framework to make the Social Web a viable source of information, through effective modeling of the credibility of peers. When peers are misguided or deceptive, our approach is able to remove these messages from consideration, for the user.

Keywords

Modeling user trust and credibility Social Web Selecting user commentary on web objects Reducing information overload 

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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • J. Champaign
    • 1
    Email author
  • R. Cohen
    • 1
  • N. Sardana
    • 1
  • J. A. Doucette
    • 1
  1. 1.University of WaterlooWaterlooCanada

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