Social Market: Combining Explicit and Implicit Social Networks

  • Davide Frey
  • Arnaud Jégou
  • Anne-Marie Kermarrec
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6976)

Abstract

The pervasiveness of the Internet has lead research and applications to focus more and more on their users. Online social networks such as Facebook provide users with the ability to maintain an unprecedented number of social connections. Recommendation systems exploit the opinions of other users to suggest movies or products based on our similarity with them. This shift from machines to users motivates the emergence of novel applications and research challenges.

In this paper, we embrace the social aspects of the Web 2.0 by considering a novel problem. We build a distributed social market that combines interest-based social networks with explicit networks like Facebook. Our Social Market (SM) allows users to identify and build connections to other users that can provide interesting goods, or information. At the same time, it backs up these connections with trust, by associating them with paths of trusted users that connect new acquaintances through the explicit network. This convergence of implicit and explicit networks yields TAPS, a novel gossip protocol that can be applied in applications devoted to commercial transactions, or to add robustness to standard gossip applications like dissemination or recommendation systems.

Keywords

Social Network Social Market Trust Information Classical Music Cluster Protocol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ahn, Y.Y., Han, S., Kwak, H., Moon, S., Jeong, H.: Analysis of topological characteristics of huge online social networking services. In: WWW (2007)Google Scholar
  2. 2.
    Bai, X.: Personalized top-k processing: from centralized to decentralized systems. Ph.D. thesis, INSA Rennes, France (2010)Google Scholar
  3. 3.
    Bender, M., Crecelius, T., Kacimi, M., Miche, S., Xavier Parreira, J., Weikum, G.: Peer-to-peer information search: Semantic, social, or spiritual? IEEE Database Engineering Bulletin 30(2) 2007Google Scholar
  4. 4.
    Bertier, M., Frey, D., Guerraoui, R., Kermarrec, A.-M., Leroy, V.: The gossple anonymous social network. In: Gupta, I., Mascolo, C. (eds.) Middleware 2010. LNCS, vol. 6452, pp. 191–211. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Birman, K.P., Hayden, M., Ozkasap, O., Xiao, Z., Budiu, M., Minsky, Y.: Bimodal multicast. ACM TOCS 17(2) (1999)Google Scholar
  6. 6.
    Boutet, A., Frey, D., Guerraoui, R., Kermarrec, A.-M.: Whatsup: News, from, for, through, everyone. In: P2P, Delft (2010)Google Scholar
  7. 7.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30(1-7) (1998)Google Scholar
  8. 8.
    Datta, A., Sharma, R.: Godisco: Selective gossip based dissemination of information in social community based overlays. In: Aguilera, M.K., Yu, H., Vaidya, N.H., Srinivasan, V., Choudhury, R.R. (eds.) ICDCN 2011. LNCS, vol. 6522, pp. 227–238. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Garriss, S., Kaminsky, M., Freedman, M.J., Karp, B., Mazières, D., Yu, H.: Re: Reliable email. In: NSDI 2006, San Jose, CA (2006)Google Scholar
  10. 10.
    Jamali, M., Ester, M.: Trustwalker: A random walk model for combining trust-based and item-based recommendation. In: KDD, Paris (2009)Google Scholar
  11. 11.
    Jelasity, M., Voulgaris, S., Guerraoui, R., Kermarrec, A.-M., van Steen, M.: Gossip-based peer sampling. ACM TOCS 25(3) (2007)Google Scholar
  12. 12.
    Jelasity, M., Babaoglu, O.: T-Man: Gossip-based overlay topology management. In: Brueckner, S.A., Di Marzo Serugendo, G., Hales, D., Zambonelli, F. (eds.) ESOA 2005. LNCS (LNAI), vol. 3910, pp. 1–15. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Jelasity, M., Montresor, A., Babaoglu, O.: Gossip-based aggregation in large dynamic networks. ACM TOCS 23(3) (2005)Google Scholar
  14. 14.
    Kuter, U., Golbeck, J.: Sunny: A new algorithm for trust inference in social networks using probabilistic confidence models. In: AAAI. AAAI Press, Menlo Park (2007)Google Scholar
  15. 15.
    Liu, Z., Hu, H., Liu, Y., Ross, K.W., Wang, Y., Mobius, M.: P2p trading in social networks: the value of staying connected. In: INFOCOM, San Diego, CA (2010)Google Scholar
  16. 16.
    Massa, P., Avesani, P.: Controversial users demand local trust metrics: an experimental study on epinions.com community. In: AAAI. AAAI Press, Menlo Park (2005)Google Scholar
  17. 17.
    Massa, P., Avesani, P.: Trust-aware recommender systems. In: RecSys. ACM, New York (2007)Google Scholar
  18. 18.
    Mislove, A., Post, A., Druschel, P., Gummadi, K.P.: Ostra: leveraging trust to thwart unwanted communication. In: NSDI, Berkeley, CA, USA (2008)Google Scholar
  19. 19.
    Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, Inc., New York (1986)MATHGoogle Scholar
  20. 20.
    Voulgaris, S., van Steen, M.: Epidemic-style management of semantic overlays for content-based searching. In: Europar, Lisbon (2005)Google Scholar
  21. 21.
    Wang, Y., Vassileva, J.: Bayesian network trust model in peer-to-peer networks. In: Moro, G., Sartori, C., Singh, M.P. (eds.) AP2PC 2003. LNCS (LNAI), vol. 2872, pp. 23–34. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  22. 22.
    Yu, H., Gibbons, P.B., Kaminsky, M., Xiao, F.: Sybillimit: a near-optimal social network defense against sybil attacks. IEEE/ACM TON 18(3) (2010)Google Scholar
  23. 23.
    Yu, H., Kaminsky, M., Gibbons, P.B., Flaxman, A.D.: Sybilguard: defending against sybil attacks via social networks. IEEE/ACM TON 16(3) (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Davide Frey
    • 1
  • Arnaud Jégou
    • 1
  • Anne-Marie Kermarrec
    • 1
  1. 1.INRIA-Rennes Bretagne AtlantiqueRennesFrance

Personalised recommendations