A syntactical approach for interpersonal trust prediction in social web applications: Combining contextual and structural data

  • Zolfaghar K
  • Aghaie A
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Abstract

Studying the social phenomena within computer science and web environment, demands more attention in recent years. In this regard, trust is a crucial basis for social interactions among users in online environment specifically social web applications in which user participation is the primary driver of value. Predicting unknown trust relationship between users is a problem addressed in this paper, using data mining and classification approach. Achieving this, we provide a framework of social trust-inducing factors that contribute in trust formation process and then we investigate the role of these factors in predicting trust between users by the results of experimental study on real data from Epinions. The experimental evaluation reveals that the proposed framework is quite feasible and promising in predicting trust connectivity with a high degree of accuracy. © 2011 Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Contextual data
  • Data mining
  • Online trust prediction
  • Social web applications
  • Structural data
  • Trust-inducing framework
  • Users interactions

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Authors

  • Kiyana Zolfaghar

  • Abdollah Aghaie

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