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Identifying the Role of Common Interests in Online User Trust Formation

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  • Lei Ji
  • Jian-Guo Liu
  • Lei Hou
  • Qiang Guo

Abstract

Despite enormous recent efforts in detecting the mechanism of the social relation formation in online social systems, the underlying rules between the common interests and social relations are still under dispute. Do online users befriend others who have similar tastes, or do their tastes become more similar after they become friends? In this paper, we investigate the correlation between online user trust formation and their common interests, measured by the overlap rate ρ and taste similarity θ respectively. The trust relation creation time is set as the zero timestamp. The statistical results before and after the trust formation for an online network, namely Epinions, show that, the overlap rate ρ increases greatly before the trust formation, while it would increase smoothly after the creation of the trust relation. Comparing with the empirical results, two null models are presented by shuffling the temporal behaviors of online users, which suggests that the accumulation of the common interests can result in the trust formation. Furthermore, we investigate the taste similarity θ of the common interests, which can reflect the users’ preference on their common interests. The empirical results show that the taste similarity θ is rapidly increased around the day when users trust the others. That is, the similar tastes on the common interests among users lead to the trust formation. Finally, we report that the user degree can also influence the effect of the taste similarity θ on user trust formation. This work may shed some light for deeply understanding the evolution mechanism of the online social systems.

Suggested Citation

  • Lei Ji & Jian-Guo Liu & Lei Hou & Qiang Guo, 2015. "Identifying the Role of Common Interests in Online User Trust Formation," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    • Handle: RePEc:plo:pone00:0121105
    DOI: 10.1371/journal.pone.0121105
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    References listed on IDEAS

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    Cited by:

    1. Hou, Lei & Liu, Kecheng & Liu, Jianguo & Zhang, Runtong, 2017. "Solving the stability–accuracy–diversity dilemma of recommender systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 415-424.
    2. Li, Sheng-Nan & Guo, Qiang & Yang, Kai & Liu, Jian-Guo & Zhang, Yi-Cheng, 2018. "Uncovering the popularity mechanisms for Facebook applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 422-429.
    3. Hongchen Wu & Xinjun Wang, 2016. "ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-21, March.
    4. Wang, Jia-Hua & Guo, Qiang & Yang, Kai & Zhang, Yi-Lu & Han, Jingti & Liu, Jian-Guo, 2016. "Popularity and user diversity of online objects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 480-486.
    5. Li, Ren-De & Liu, Jian-Guo & Guo, Qiang & Zhang, Yi-Cheng, 2018. "Social signature identification of dynamical social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 213-222.
    6. Guo, Xin-Yu & Guo, Qiang & Li, Ren-De & Liu, Jian-Guo, 2018. "Long-term memory of rating behaviors for the online trust formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 254-264.

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