The Influence of Interaction Attributes on Trust in Virtual Communities

نویسندگان

  • Lizi Zhang
  • Cheun Pin Tan
  • Siyi Li
  • Hui Fang
  • Pramodh Rai
  • Yao Chen
  • Rohit Luthra
  • Wee Keong Ng
  • Jie Zhang
چکیده

In virtual communities (e.g., forums, blogs), modeling the trust of community members is an effective way to help members make decisions about whose information is more valuable. Towards this goal, we first formulate hypotheses on how various interaction attributes influence trust in virtual communities, and validate these hypotheses through experiments on real data. The influential attributes are then used to develop a trust ranking-based recommendation model called TruRank for recommending the most trustworthy community members. Contrary to traditional recommender systems that rely heavily on subjective manual feedback, our model is built on the foundation of carefully verified objective interaction attributes in virtual communities.

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تاریخ انتشار 2011