Skip to main content

HySoN: A Distributed Agent-Based Protocol for Group Formation in Online Social Networks

  • Conference paper
Book cover Multiagent System Technologies (MATES 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8076))

Included in the following conference series:

Abstract

On-line social networks allow people to easily interact with each other by means of social computer services. This scenario makes possible to search in a social network for affinities or new opportunities that satisfy specific requirements. However, for many users such activities often imply undesirable accesses to personal sensitive data. In this scenario we propose a novel approach, called HySoN (Hyperspace Social Network), based on an overlay network of software agents. HySoN allows users to locally maintain sensitive user’s data, satisfying the privacy requirements preserving sensitive data. Indeed, the properties involved in the HySoN user aggregation are inferred by local data not published in the social network. Some experimental results obtained on simulated on-line social networks data show the searching of suitable nodes is very efficient due to the topology of the overlay network, which exhibits the small-world properties.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anagnostopoulos, A., Becchetti, L., Castillo, C., Gionis, A., Leonardi, S.: Power in unity: forming teams in large-scale community systems. In: Proc. 19th ACM Int. Conf. on Information and Knowledge Management, pp. 599–608. ACM (2010)

    Google Scholar 

  2. Anagnostopoulos, A., Becchetti, L., Castillo, C., Gionis, A., Leonardi, S.: Online team formation in social networks. In: Proc. 21st Int. Conf. on WWW, pp. 839–848. ACM (2012)

    Google Scholar 

  3. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R.H., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Stoica, I., et al.: Above the clouds: A Berkeley view of cloud computing. EECS Dept., University of California, Berkeley, Tech. Rep. UCB/EECS-2009-28 (2009)

    Google Scholar 

  4. Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: membership, growth, and evolution. In: Proc. 12th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, pp. 44–54. ACM (2006)

    Google Scholar 

  5. Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)

    Article  MathSciNet  Google Scholar 

  6. Berkhin, P.: A survey of clustering data mining techniques. In: Grouping Multidimensional Data, pp. 25–71. Springer (2006)

    Google Scholar 

  7. Brandes, U., Gaertler, M., Wagner, D.: Engineering graph clustering: Models and experimental evaluation. ACM J. of Experimental Algorithmics 12(1.1), 1–26 (2007)

    MathSciNet  Google Scholar 

  8. Buccafurri, F., Palopoli, L., Rosaci, D., Sarné, G.M.L.: Modeling cooperation in multi-agent communities. Cognitive Systems Research 5(3), 171–190 (2004)

    Article  Google Scholar 

  9. Bulatov, A.A.: Complexity of conservative constraint satisfaction problems. ACM Transactions on Computational Logic (TOCL) 12(4), 24 (2011)

    Article  MathSciNet  Google Scholar 

  10. Burt, R.S.: Structural holes: The social structure of competition. Harvard Univ. Press (2009)

    Google Scholar 

  11. Carrington, P.J., Scott, J., Wasserman, S.: Models and methods in social network analysis. Cambridge Univ. Press (2005)

    Google Scholar 

  12. Castells, M.: The Internet galaxy: Reflections on the Internet, business, and society. Taylor & Francis (2003)

    Google Scholar 

  13. Chhabra, M., Das, S., Szymanski, B.: Team formation in social networks. In: Computer and Information Sciences III, pp. 291–299. Springer (2013)

    Google Scholar 

  14. Costa, P., Napper, J., Pierre, G., van Steen, M.: Autonomous resource selection for decentralized utility computing. In: 29th IEEE Int. Conf. on Distributed Computing Systems, ICDCS 2009, pp. 561–570. IEEE (2009)

    Google Scholar 

  15. Talia, D., Trunfio, P.: Toward a synergy between p2p and grids. IEEE Internet Computing 7(4), 94–96 (2003)

    Article  Google Scholar 

  16. Ferber, J.: Multi-agent systems: an introduction to distributed artificial intelligence, vol. 1. Addison-Wesley Reading (1999)

    Google Scholar 

  17. Furht, B., Escalante, A.: Handbook of cloud computing. Springer (2010)

    Google Scholar 

  18. Gaertler, M.: Clustering. In: Brandes, U., Erlebach, T. (eds.) Network Analysis. LNCS, vol. 3418, pp. 178–215. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  19. Gajewar, A., Sarma, A.D.: Multi-skill collaborative teams based on densest subgraphs. In: SDM 2012 (2011)

    Google Scholar 

  20. Gaston, M.E., desJardins, M.: Agent-organized networks for dynamic team formation. In: Proc. 4th int. Conf. on Autonomous Agents and Multiagent Sys., pp. 230–237. ACM (2005)

    Google Scholar 

  21. Giunta, R., Messina, F., Pappalardo, G., Tramontana, E.: Providing qos strategies and cloud-integration to web servers by means of aspects. Concurrency and Computation: Practice and Experience (2013), doi:10.1002/cpe.3031

    Google Scholar 

  22. Holme, P., Newman, M.E.J.: Nonequilibrium phase transition in the coevolution of networks and opinions. Physical Review E 74(5), 056108 (2006)

    Article  Google Scholar 

  23. Hopcroft, J., Khan, O., Kulis, B., Selman, B.: Tracking evolving communities in large linked networks. Proc. of the National Academy of Sciences of the USA 101(sup. 1), 5249–5253 (2004)

    Article  Google Scholar 

  24. Howard, B.: Analyzing online social networks. Comm. of the ACM 51(11), 14–16 (2008)

    Article  Google Scholar 

  25. Huebscher, M.C., McCann, J.A.: A survey of autonomic computing: degrees, models, and applications. ACM Computing Surveys 40(3), 7 (2008)

    Article  Google Scholar 

  26. Iamnitchi, A., Foster, I.: A peer-to-peer approach to resource location in grid environments. In: Grid Resource Management, Kluwer Pub. (2003)

    Google Scholar 

  27. Jackson, M.O.: A survey of network formation models: Stability and efficiency. In: Group Formation in Economics: Networks, Clubs and Coalitions, pp. 11–57 (2005)

    Google Scholar 

  28. Kannan, R., Vempala, S., Vetta, A.: On clusterings: Good, bad and spectral. J. of the ACM (JACM) 51(3), 497–515 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  29. Klusch, M.: Information agent technology for the internet: a survey. Data & Knowledge Engineering 36(3), 337–372 (2001)

    Article  MATH  Google Scholar 

  30. Lappas, T., Liu, K., Terzi, E.: Finding a team of experts in social networks. In: Proc. 15th SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, pp. 467–476. ACM (2009)

    Google Scholar 

  31. Li, C.T., Shan, M.K.: Team formation for generalized tasks in expertise social networks. In: 2010 IEEE 2nd Int. Conf. on Social Computing (SocialCom), pp. 9–16. IEEE (2010)

    Google Scholar 

  32. Marx, K., Bottomore, T.B., Rubel, M., Fromm, E.: Selected writings in sociology & social philosophy. McGraw-Hill, New York (1964)

    Google Scholar 

  33. Messina, F., Pappalardo, G., Rosaci, D., Santoro, C., Sarné, G.M.L.: A trust-based approach for a competitive cloud/Grid computing scenario. In: Fortino, G., Badica, C., Malgeri, M., Unland, R. (eds.) Intelligent Distributed Computing VI. SCI, vol. 446, pp. 129–138. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  34. Messina, F., Pappalardo, G., Santoro, C.: Hygra: A decentralized protocol for resource discovery and job allocation in large computational grids. In: 2010 IEEE Symposium on Computers and Communications (ISCC), pp. 817–823. IEEE (2010)

    Google Scholar 

  35. Messina, F., Pappalardo, G., Santoro, C.: Exploiting the Small-World Effect for Resource Finding in P2P Grids/Clouds. In: Proc. 20th IEEE Int. Work. on Enabling Technologies: Infrastructures for Collaborative Enterprises, pp. 122–127 (2011)

    Google Scholar 

  36. Messina, F., Pappalardo, G., Santoro, C.: Complexsim: An smp-aware complex network simulation framework. In: 2012 6th Int. Conf. on Complex, Intelligent and Software Intensive Systems (CISIS), pp. 861–866. IEEE (2012)

    Google Scholar 

  37. Messina, F., Pappalardo, G., Santoro, C.: Decentralised resource finding in cloud/grid computing environments: A performance evaluation. In: IEEE 21st Int. Work. on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp. 143–148. IEEE (2012)

    Google Scholar 

  38. Messina, F., Pappalardo, G., Santoro, C.: Complexsim: a flexible simulation platform for complex systems. International J. of Simulation and Process Modelling (2013)

    Google Scholar 

  39. Perer, A., Shneiderman, B.: Balancing systematic and flexible exploration of social networks. IEEE Transactions on Visualization and Computer Graphics 12(5), 693–700 (2006)

    Article  Google Scholar 

  40. Postmes, T., Spears, R., Lea, M.: The formation of group norms in computer-mediated communication. Human Communication Research 26(3), 341–371 (2000)

    Article  Google Scholar 

  41. Rosaci, D., Sarné, G.M.L.: Matching users with groups in social networks. In: Zavoral, F., Jung, J.J., Badica, C. (eds.) Intelligent Distributed Computing VII. SCI, vol. 511, pp. 45–54. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  42. Rosaci, D., Sarnè, G.M.L., Garruzzo, S.: Integrating trust measures in multiagent systems. International Journal of Intelligent Systems 27(1), 1–15 (2012)

    Article  Google Scholar 

  43. Sarkar, P., Moore, A.W.: Dynamic social network analysis using latent space models. ACM SIGKDD Explorations Newsletter 7(2), 31–40 (2005)

    Article  Google Scholar 

  44. Schaeffer, S.E.: Graph clustering. Computer Science Review 1(1), 27–64 (2007)

    Article  MathSciNet  Google Scholar 

  45. Sofia Pereira, C., Soares, A.L.: Improving the quality of collaboration requirements for information management through social networks analysis. Int. J. of Information Management 27(2), 86–103 (2007)

    Article  Google Scholar 

  46. Steinhaeuser, K., Chawla, N.V.: Identifying and evaluating community structure in complex networks. Pattern Recognition Letters 31(5), 413–421 (2010)

    Article  Google Scholar 

  47. Wasserman, S., Faust, K.: Social network analysis: Methods and applications, vol. 8. Cambridge univ. press (1994)

    Google Scholar 

  48. Watts, D., Strogatz, S.J.: Collective Dynamics of ‘Small-World’ Networks. Nature 393(6684), 440–442 (1998)

    Article  Google Scholar 

  49. Yang, W.S., Dia, J.B., Cheng, H.C., Lin, H.T.: Mining social networks for targeted advertising. In: Proc. 39th Annual Hawaii Int. Conf. on System Sciences, HICSS 2006, vol. 6, p. 137a. IEEE (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Messina, F., Pappalardo, G., Rosaci, D., Santoro, C., Sarné, G.M.L. (2013). HySoN: A Distributed Agent-Based Protocol for Group Formation in Online Social Networks. In: Klusch, M., Thimm, M., Paprzycki, M. (eds) Multiagent System Technologies. MATES 2013. Lecture Notes in Computer Science(), vol 8076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40776-5_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40776-5_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40775-8

  • Online ISBN: 978-3-642-40776-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics