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A trust evaluation scheme for complex links in a social network: a link strength perspective

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Abstract

Potential security threats pose a significant challenge to evaluating the trustworthiness of complex links among users in a social network. Traditional trust computation methods typically consider user comments or interaction, thereby reflecting the trustworthiness between users according to their past experiences. However, the tie strength, which reflects the closeness of user relationships, is also a potential factor for estimating the trustworthiness of links among users. To incorporate this indicator, we propose a trust evaluation scheme for complex links comprising two aspects: the reliability and strength of links among uses. Our main contributions are (1) a trust calculation method, including direct trust for directly linked users and indirect trust for indirectly linked users, which is established based on the comment factor, forwarding factor, and approving factor; (2) a link strength evaluation method to determine the trustworthiness of direct and indirect links between users considering comment stability, mutual trust, interaction frequency, and common neighbours and community similarity, and (3) a link trust evaluation algorithm based on the link trust matrix synthesizing the reliability and strength of links. The experimental results and analysis show that our proposed scheme is feasible and effective in improving the performance of trust evaluation in a social network.

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References

  1. Watts Duncan J, Gueorgi K (2006) Empirical Analysis of an Evolving Social Network. Science 311(5757):88–90

  2. Groenewegen P, Moser C (2014) Online communities: Challenges and opportunities for social network research. Res Sociol Organ 40:463–477

    Article  Google Scholar 

  3. Chang W-L et al (2014) Estimating trust value: A social network perspective. Inf Syst Front, pp 1–20

  4. Jøsanga A, Ismailb R, Boydb C (2007) A survey of trust and reputation systems for online service provision. Decis Support Syst 43(2):618–644

    Article  Google Scholar 

  5. Sabater J, Sierra C (2005) Review on Computational Trust and Reputation Models. Artificial Intelligence Review 24(1):33–60

    Article  MATH  Google Scholar 

  6. Faisal M et al (2014) Trust inference algorithms for social networks. J Eng Res 2:29–48

    Article  Google Scholar 

  7. González-Manzano L et al (2014) Extended U + F Social Network Protocol: Interoperability, reusability, data protection and indirect relationships in Web Based Social Networks. J Syst Softw:50–71

  8. See-To EWK, Ho KKW (2014) Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust-A theoretical analysis. Comput Hum Behav 31:182–189

    Article  Google Scholar 

  9. Gang W, Xiaolin G (2013) Selecting and Trust Computing for Transaction Nodes in Online Social Networks. Chinese Journal of Computers 36(2):368–383

    MathSciNet  Google Scholar 

  10. Jian W, Chiclana F (2014) A social network analysis trust consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations. Knowl-Based Syst 59:97–107

    Article  Google Scholar 

  11. Nepal S et al (2015) Behavior-based propagation of trust in social networks with restricted and anonymous participation. Comput Intell 31(4):624–668

  12. Basit Q, Geyong M (2012) Kouvatsos Demetres. Trusted information exchange in peer-to-peer mobile social networks. Concurrency and Computation-Practice & Experience 24(17): 2055–2068

    Article  Google Scholar 

  13. Zhao H, Li X (2013) VectorTrust: trust vector aggregation scheme for trust management in peer-to-peer networks. J Supercomput 64.3:805–829

    Article  Google Scholar 

  14. Golbeck J (2009) Trust and nuanced profile similarity in online social networks. ACM Trans Web 3(4). [Article 12]

  15. Deng S, Huang L, Xu G (2014) Social network-based service recommendation with trust enhancement. Expert Syst Appl 41.18:8075–8084

    Article  Google Scholar 

  16. Lim E-P et al (2013) Finding the Optimal Social Trust Path for the Selection of Trustworthy Service Providers in Complex Social Networks. IEEE Trans Serv Comput 6.2:152–167

    Google Scholar 

  17. Tang M et al (2014) Combining Global and Local Trust for Service Recommendation. In: 2014 IEEE International Conference on Web Services (ICWS). IEEE

  18. Jiang W et al (2014) Generating trusted graphs for trust evaluation in online social networks. Futur Gener Comput Syst 31.1:48–58

    Article  Google Scholar 

  19. Ae KY, Rasik P (2012) A trust prediction framework in rating-based experience sharing social networks without a Web of Trust. Inf Sci 191(5):128–145

    MATH  Google Scholar 

  20. Yu-lin H et al (2015) OWA operator based link prediction ensemble for social network. Expert Systems with Applications 42:21–50

    Article  Google Scholar 

  21. Li N et al (2013) Modeling Relationship Strength for Link Prediction. Intelligence and Security Informatics. Springer, Berlin, pp 62–74

    Book  Google Scholar 

  22. Xiang R et al (2010) Modeling relationship strength in online social networks. In: Proceedings of WWW ’10 , pp 981–990

  23. Yanagimoto H, Yoshioka M (2012) Relationship Strength Estimation for Social Media Using Folksonomy and Network Analysis. In: IEEE World Congress on Computational Intelligence, WCCI 2012, Brisbane, pp 1–8

  24. Inay H (2013) Link Strength-Based Collaborative Filtering for Enhancing Prediction Accuracy. In: 2013 International Conference on Information Science and Applications. IEEE, pp 1–4

  25. Fogués RL et al (2014) BFF: A tool for eliciting tie strength and user communities in social networking services. Inf Syst Front 16.2:225–237

    Article  Google Scholar 

  26. Lin X, Shang T, Liu J (2014) An Estimation Method for Relationship Strength in Weighted Social Network Graphs. Journal of Computer and Communications 2.04:82

    Google Scholar 

  27. Zhao X et al (2012) Relationship strength estimation for online social networks with the study on Facebook. Neurocomputing 95.14:89–97

    Article  Google Scholar 

  28. Zhao J et al (2012) Information propagation in online social networks: a tie-strength perspective. Knowl Inf Syst 32.3:589–608

    Article  Google Scholar 

  29. Kamvar SD, Schlosser MT (2003) EigenRep: Reputation management in P2P networks. In: Proceedings of the 12th Int’l World Wide Web Conf., pp 123–134

  30. Selcuk AA, Uzun E, Pariente MR (2004) A reputation based trust management system for P2P networks CCGrid 2004. In: IEEE International Symposium on Cluster Computing and the Grid, 2004. IEEE

  31. Bahtiyar S, Cihan M, Caglayan MU (2010) A model of security information flow on entities for trust computation. In: 2010 IEEE 10th International Conference on Computer and Information Technology (CIT). IEEE

  32. Zhang B, Huang Z, Yu J, Xiang Y (2014) Trust computation for Multiple Routes Recommendation in Social Network Sites. Security and Communication Networks:1

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Acknowledgments

This work is funded by National Basic Research Program of China (2014CB340404), National Natural Science Foundation of China (61572326, 61103069, 71171148, and 61272268), Innovation Program of Shanghai Municipal Education Commission (13YZ052), and the Shanghai Rising-Star Program (No. 15QA1403900) for supports.

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Authors and Affiliations

  1. College of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China

    Meizi Li, Yang Xiang, Zhenhua Huang & Jiawen Zhang

  2. College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, 200234, China

    Meizi Li & Bo Zhang

Authors
  1. Meizi Li
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  2. Yang Xiang
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  3. Bo Zhang
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  4. Zhenhua Huang
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  5. Jiawen Zhang
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Corresponding author

Correspondence to Bo Zhang.

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Li, M., Xiang, Y., Zhang, B. et al. A trust evaluation scheme for complex links in a social network: a link strength perspective. Appl Intell 44, 969–987 (2016). https://doi.org/10.1007/s10489-015-0734-2

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  • DOI: https://doi.org/10.1007/s10489-015-0734-2

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