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Volume 27 Issue 3
May  2012
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Yu Zhang, Tong Yu. Mining Trust Relationships from Online Social Networks[J]. Journal of Computer Science and Technology, 2012, 27(3): 492-505. DOI: 10.1007/s11390-012-1238-8
Citation: Yu Zhang, Tong Yu. Mining Trust Relationships from Online Social Networks[J]. Journal of Computer Science and Technology, 2012, 27(3): 492-505. DOI: 10.1007/s11390-012-1238-8
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Mining Trust Relationships from Online Social Networks

  • 1. School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China;
    2. College of Computer Science, Zhejiang University, Hangzhou 310027, China

Funds: This work is supported by the National Natural Science Foundation of China under Grant No. 61100183, the Natural Science Foundation of Zhejiang Province of China under Grant No. Y1110477, and the Science Foundation of Zhejiang Sci-Tech University under Grant No. 0907838-Y.
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  • Author Bio:

    Yu Zhang is an associate pro-fessor of Zhejiang Sci-Tech Univer-sity, China. She received her Ph.D. degree from Zhejiang University in 2009. She is a member of CCF and ACM. Her current research interests include trust computing, Semantic Web and online social network anal-ysis.

  • Received Date: August 30, 2011
  • Revised Date: December 17, 2011
  • Published Date: May 04, 2012
    Abstract
  • With the growing popularity of online social network, trust plays a more and more important role in connecting people to each other. We rely on our personal trust to accept recommendations, to make purchase decisions and to select transaction partners in the online community. Therefore, how to obtain trust relationships through mining online social networks becomes an important research topic. There are several shortcomings of existing trust mining methods. First, trust is category-dependent. However, most of the methods overlook the category attribute of trust relationships, which leads to low accuracy in trust calculation. Second, since the data in online social networks cannot be understood and processed by machines directly, traditional mining methods require much human effort and are not easily applied to other applications. To solve the above problems, we propose a semantic-based trust reasoning mechanism to mine trust relationships from online social networks automatically. We emphasize the category attribute of pairwise relationships and utilize Semantic Web technologies to build a domain ontology for data communication and knowledge sharing. We exploit role-based and behavior-based reasoning functions to infer implicit trust relationships and category-specific trust relationships. We make use of path expressions to extend reasoning rules so that the mining process can be done directly without much human effort. We perform experiments on real-life data extracted from Epinions. The experimental results verify the effectiveness and wide application use of our proposed method.
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    • References (29)
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