Wednesday , June 20 2018

Trust and Reputation Model for Various Online Communities

Computer Science Department, Alexandru Ioan Cuza University of Iasi
16,Berthelot, Iasi, Romania

Mircea – F. VAIDA
Communication Department, Technical University Of Cluj-Napoca
26-28, Gh. Baritiu Street, Cluj-Napoca, Romania

Abstract: In World Wide Web there are many online communities with a huge number of users and a great amount of data which are continuously increasing. In this context it is important for users to interact with resources and other users according to their preferences. On this direction of information filtering domain our work is oriented to trust based filtering. We have developed a model formed by three interconnected components: trust component which allows computation of trust levels among users which are not directly connected, a component which computes reputation of entities in the system, and a recommendation component. Several sets of tests of our model have been performed and we have the possibility to integrate it in various online communities.

Keywords: Online community, social trust, local trust metric, reputation, recommendations.

>>Full text
Lenuta ALBOAIE, Mircea-F. VAIDA, Trust and Reputation Model for Various Online Communities, Studies in Informatics and Control, ISSN 1220-1766, vol. 20 (2), pp. 143-156, 2011.

1. Introduction

The existing technologies have led to an increasing interaction between people who do not know each other. In this case, online interactions replace human interactions. An important goal of our article is to improve these interactions based on two important concepts: social trust and reputation.

Trust and reputation are two interrelated concepts. We can find trust at personal level. Reputation expresses an opinion resulting from collective opinions of community members. This type of evaluation may lead to risks such as penalty of innovative and minority ideas, problem described in (Tocqueville 1840), (Massa, Avesani 2007) as “tyranny of the majority”. Naturally, the opinions of minority groups matter and should be seen as opportunities. But if minority groups obtain a full priority, it is obtained the other extreme, the so-called phenomenon of “echo chamber”. In this case, as shown in (Sunstein 2009) will result a fragmentation of society into micro-groups that tend to sustain extremely their opinions.

Nowadays, there are many online communities (community for sharing resources, social networks, scientific communities, etc.), that store a great amount of data which are continuously increasing. Anyone can publish any kind of resources: a diary published within a blog, a track that a user wants to make public, etc.

In this context in which users have to interact with other users about whom they don’t have any previous information, and in which the overloaded information phenomenon brings a major impact, this paper comes up with a solution to improve the interactions among users and resources management.

The proposed trust and reputation model assures that users experience resulted from the previous interactions are used to establish user-user and user-resource evaluation levels.

Therefore, the purpose of the paper is to find a solution based on trust and reputation to provide users from online communities a balanced combination of personal vision with a global perspective on the community that will provide the opportunity to interact with users and resources that are relevant to them.

Section 2 presents the trust and reputation concept and the main proposals that exist in the scientific literature. Section 3 presents our trust and reputation model based on a set of published results (Alboaie 2008), (Alboaie, Barbu 2008), (Alboaie, Vaida 2010).

Section 4 provides details about our model architecture and the results obtained from several tests are presented. A comparison with the most relevant local trust metric, Mole Trust has been performed. Section 5 will contain the conclusions and the future work.


  1. ALBOAIE, L. PReS – Personalized Evaluation System in a WEB Community, Proceedings of the International Conference on E-Business, 2008, pp. 64-69.
  2. ALBOAIE, L., T. BARBU, An Automatic User Recognition Approach within a Reputation System Using a Nonlinear Hausdorff Derived Metric, Numerical Functional Analysis and Optimization, Pub. Taylor & Francis, Vol. 29, Issue 11 & 12, 2008, pp. 1240-1251
  3. ALBOAIE, L., Studies on Trust Modeling and Computation of Reputation in Online Communities, Ph.D. thesis, Al. I. Cuza University, Iasi, 2009
  4. ALBOAIE, L., S. BURAGA, Trust and Reputation in e-Health Systems, Proceedings of the International Conference on Advancements of Medicine and Health Care through Technology; IFMBE Cluj-Napoca, vol. 26, 2009, pp. 43-46.
  5. ALBOAIE, L., M.-F. VAIDA, Modeling of Trust to Provide Users Assisted Secure Actions in Online Communities, NDT, Communications in Computer and Information Science of Springer Lecture Notes, Prague, Series-87, 2010, pp. 369-382.
  6. BERNERS-LEE, T., et al., Uniform Resource Identifiers (URI) , General Syntax, RFC 2396, IETF, 1998.
  7. BREABAN, M., L. ALBOAIE, H. LUCHIAN, Guiding Users within Trust Networks Using Swarm Algorithms, IEEE Congress on Evolutionary Computation (IEEE CEC 2009), 2009, pp. 1770-1777.
  8. CHIOREAN, L. D., L. SUTA, M.-F. VAIDA, M. HEDESIU, Medical Fusion Components for a Web Dedicated Application, Studies in Informatics and Control, Vol. 19, Issue 4, 2010, pp. 435-444, ISSN 1220-1766.
  9. GAMBETTA, D., Trust: Making and Breaking Cooperative Relations; Can We Trust Trust? , Basil Blackwell, 2000, pp. 213-237.
  10. GOLBECK, J., Personalizing Applications through Integration of Inferred Trust Values in Semantic Web-Based Social Networks, Proceedings of the Semantic Network Analysis Workshop at the 4th Intl. Semantic Web Conference, Galway 2005.
  11. GOLBECK, J., Computing and Applying Trust in Web-based Social Networks PhD thesis, Univ. of Maryland, 2005.
  12. GOLBECK, J., Computing with Social Trust, Springer Publisher, 2009, pp. 338.
  13. GUHA, R., Open Rating Systems, Technical report, Stanford Knowledge Systems Laboratory, Stanford, CA, USA, 2003.
  14. HARDIN, R., Trust and Trustworthiness, Russell Sage Foundation, New York, 2002.
  15. HARMON, A., Amazon Glitch Unmasks War of Reviewers, The New York Times, 14 February 2004.
  16. JOSANG, A., R. ISMAIL, C. BOYD, A Survey of Trust and Reputation Systems for Online Service Provision, Decision Support Systems, Vol.43, no.2, Elsevier Science Publishers., 2007, pp. 618-644
  17. LEVIEN, R., Attack Resistant Trust Metrics, PhD thesis, UC Berkeley, Berkeley, CA, USA, 2003.
  18. MASSA, P., P. AVESANI, Controversial Users Demand Local Trust Metrics: an Experimental Study on Community, Proceeding of the 25th Conference, 2005, pp. 121-126.
  19. MASSA, P., P. AVESANI, Trust-Aware Bootstrapping of Recommender Systems, ECAI’06 Workshop on Recommender Systems, 2006, pp. 29-33.
  20. MASSA, P., P. AVESANI, Trust Metrics on Controversial Users: Balancing Between Tyranny of The Majority and Echo Chambers, Intl. Journal on Semantic Web and Information Systems, vol. 3(1), 2007, pp. 39-64.
  21. MUI, L., M. MOHTASHEMI, A. HALBERSTADT, A Computational Model of Trust and Reputation, Proceedings of the 35th Annual Hawaii Intl. Conference on System Sciences, 2002, pp. 2431- 2439.
  22. NURMI, P., A Bayesian Framework for Online Reputation Systems, AICT-ICIW’06, 2006, p. 121.
  23. PAGE, L., S. BRIN, R. MOTWANI, T. WINOGRAD, The PageRank Citation Ranking: Bringing Order to the Web, Technical report, Stanford Digital Library Technologies Project, 1998.
  24. RAHMAN, A., S. HAILES, Supporting Trust in Virtual Communities, System Sciences, Proceedings of the 33rd Annual Hawaii Intl. Conference on System Sciences, vol. 1, 2000, p. 9. S
  25. ABATER, J., C. SIERRA, Social ReGreT, a Reputation Model Based on Social Relations, SIGecom Exchanges 3.1, 2002, pp. 44-56.
  26. SEPANDAR, D. K., M. T. SCHLOSSER, H. GARCIA-MOLINA, The Eigentrust Algorithm for Reputation Management in P2P Networks, 12th Intl. Conf. on World Wide Web, 2003, pp. 640-651.
  27. SUNSTEIN, C. R., 2.0, Princeton University Press, 2009, p. 241.
  28. DE TOCQUEVILLE, A., Democracy in America, The Library of America, New York, 1835-1840
  29. ZIEGLER, C., G. LAUSEN, Analyzing Correlation between Trust and User Similarity in Online Communities, 2nd Intl. Conf. on Trust Management, Springer, 2004, pp. 251-265.
  30. WU, Z., X. YU, J. SUN, An Improved Trust Metric for Trust-Aware Recommender Systems, First Intl. Workshop on Education Technology and Computer Science, vol. 1, 2009, pp. 947-951.