A Node-Centric Reputation Computation Algorithm on Online Social Networks

  • JooYoung Lee
  • Jae C. Oh
Part of the Lecture Notes in Social Networks book series (LNSN)


In online social networks, reputations of users (nodes) are emerged and propagated through interactions among the users. These interactions include intrinsic and extrinsic consensus (voting) among neighboring users influenced by the network topology. We introduce an algorithm that considers the degree information of nodes (users) to model how reputations spread within the network. In our algorithm, each node updates reputations about its neighbors by considering the history of interactions and the frequency of the interactions in recent history. The algorithm also captures the phenomena of accuracy of reputations deteriorating over time if interactions have not occurred recently. We present the following two contributions through experiments: (1) We show that an agent’s reputation value is influenced by the position of the node in the network and the neighboring topology; and (2) We also show that our algorithm can compute more accurate reputations than existing algorithms especially when the topological information matters. The experiments are conducted in random social networks and Autonomous Systems Network of the Internet. In addition, we show the efficacies of each component in our algorithm and present their effects on the algorithm.


Reputation management Multi-agent systems Propagation of information Trust in autonomous systems 


  1. 1.
    Carbo J, Molina JM, Davila J (2003) Trust management through fuzzy reputation. Int J Coop Inf Syst 12(01):135–155CrossRefGoogle Scholar
  2. 2.
    Sabater J, Sierra C (2001) Regret: reputation in gregarious societies. In: Proceedings of the fifth international conference on autonomous agents. AGENTS ’01. ACM Press, New York, pp 194–195Google Scholar
  3. 3.
    Zacharia G (2000) Trust management through reputation mechanisms. Appl Artif Intell 14:881–907CrossRefGoogle Scholar
  4. 4.
    Lee JY, Oh JC (2013) A model for recursive propagations of reputations in social networks. In: Proceedings of the 2013 IEEE/ACM international conference on advances in social networks analysis and mining. ASONAM ’13. ACM Press, New York, pp 666–670Google Scholar
  5. 5.
    Galan J, Latek M, Rizi S (2011) Axelrod’s metanorm games on networks. PLoS One 6(5):e20474CrossRefGoogle Scholar
  6. 6.
    Galeotti A, Goyal S, Jackson MO, Vega-Redondo F, Yariv L (2010) Network games. Rev Econ Stud 77(1):218–244Google Scholar
  7. 7.
    Szabo G, Fath G (2007) Evolutionary games on graphs. Phys Rep 446(4–6):97–216CrossRefMathSciNetGoogle Scholar
  8. 8.
    Pinyol I, Sabater-Mir J (2011) Computational trust and reputation models for open multi-agent systems: a review. Artif Intell Rev, 40(1):1–25Google Scholar
  9. 9.
    Huynh TD, Jennings NR, Shadbolt NR (2004) Fire: an integrated trust and reputation model for open multi-agent systems. In: Proceedings of the 16th european conference on artificial intelligence (ECAI), pp 18–22Google Scholar
  10. 10.
    Teacy WTL, Patel J, Jennings NR, Luck M (2006) Travos: trust and reputation in the context of inaccurate information sources. J Auton Agents Multi-Agent Syst 12:2006CrossRefGoogle Scholar
  11. 11.
    Xiong L, Liu L (2004) Peertrust: supporting reputation-based trust for peer-to-peer electronic communities. IEEE Trans Knowl Data Eng 16:843–857CrossRefGoogle Scholar
  12. 12.
    Lee J, Duan Y, Oh JC, Du W, Blair H, Wang L, Jin X (2012) Social network based reputation computation and document classification. j-jucs 18(4):532–553Google Scholar
  13. 13.
    Chang J, Venkatasubramanian KK, West AG, Kannan S, Lee I, Loo BT, Sokolsky O (2012) As-cred: reputation and alert service for interdomain routing. IEEE J Syst, 1:99Google Scholar
  14. 14.
    University of Oregon RouteViews project.
  15. 15.
  16. 16.
    Leskovec J, Faloutsos C (2006) Sampling from large graphs. In: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining. KDD ’06, ACM Press, New York, pp 631–636Google Scholar
  17. 17.
    Chang J, Venkatasubramanian K, West A, Kannan S, Loo B, Sokolsky O, Lee I (2011) As-trust: a trust quantification scheme for autonomous systems in bgp. In: McCune J, Balacheff B, Perrig A, Sadeghi AR, Sasse A, Beres Y (eds) Trust and trustworthy computing. Lecture notes in computer science, vol 6740. Springer, Heidelberg, pp 262–276Google Scholar
  18. 18.
    The CAIDA AS Relationships dataset, January 1, 2010—January 31, 2010.
  19. 19.
    Butler K, Farley T, McDaniel P, Rexford J (2010) A survey of bgp security issues and solutions. Proc IEEE 98(1):100–122Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Computer Science Syracuse UniversitySyracuseNew York

Personalised recommendations