Advertisement

Mining Personal Social Features in the Community of Email Users

  • Przemysıaw Kazienko
  • Katarzyna Musiał
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4910)

Abstract

The development of structure analysis that constitutes the core part of social network analysis is continuously supported by the rapid expansion of different kinds of social networks available in the Internet. The network analyzed in this paper is built based on the email communication between people. Exploiting the data about this communication some personal social features can be discovered, including personal position that means individual importance within the community. The evaluation of position of an individual is crucial for user ranking and extraction of key network members.

The new method of personal importance analysis is presented in the paper. It takes into account the strength of relationships between network members, its dynamic as well as personal position of the nearest neighbours. The requirements for the commitment function that reflects the strength of the relationship are also specified. In order to validate the proposed method, the dataset containing Enron emails is utilized; first to build the virtual social network and afterwards to assess the position of the network members.

Keywords

email communication user ranking social network analysis personal importance social features in community 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Adamic, L.A., Adar, E.: Friends and Neighbors on the Web. Social Networks 25(3), 211–230 (2003)CrossRefGoogle Scholar
  2. 2.
    Bavelas, A.: Communication patterns in task – oriented groups. Journal of the Acoustical Society of America 22, 271–282 (1950)CrossRefGoogle Scholar
  3. 3.
    Botafogo, R.A., Rivlin, E., Shneiderman, B.: Structural analysis of hypertexts: identifying hierarchies and useful metrics. ACM Transaction on Information Systems 10(2), 142–180 (1992)CrossRefGoogle Scholar
  4. 4.
    Berkhin, A.: A Survey on PageRank Computing. Internet Mathematics 2(1), 73–120 (2005)zbMATHMathSciNetGoogle Scholar
  5. 5.
    Boyd, D.M.: Friendster and Publicly Articulated Social Networking. In: CHI 2004, pp. 1279–1282. ACM Press, New York (2004)CrossRefGoogle Scholar
  6. 6.
    Brin, S., Page, L.: The Anatomy of a Large-Scale Hypertextual Web Search Engine. Computer Networks and ISDN Systems 30(1–7), 107–117 (1998)CrossRefGoogle Scholar
  7. 7.
    Brinkmeier, M.: PageRank Revisited. ACM Transactions on Internet Technology 6(3), 282–301 (2006)CrossRefGoogle Scholar
  8. 8.
    Culotta, A., Bekkerman, R., McCallum, A.: Extracting social networks and contact information from email and the Web. In: CEAS 2004, First Conference on Email and Anti-Spam (2004)Google Scholar
  9. 9.
    Freeman, L.C.: Centrality in social networks: Conceptual clarification. Social Networks 1(3), 215–239 (1979)CrossRefGoogle Scholar
  10. 10.
    Garton, L., Haythorntwaite, C., Wellman, B.: Studying Online Social Networks. Journal of Computer-Mediated Communication 3(1) (1997)Google Scholar
  11. 11.
    Gibson, D., Kleinberg, J., Raghavan, P.: Inferring Web communities from link topology. In: 9th ACM Conference on Hypertext and Hypermedia, pp. 225–234 (1998)Google Scholar
  12. 12.
    Golbeck, J., Hendler, J.A.: Accuracy of Metrics for Inferring Trust and Reputation in Semantic Web-Based Social Networks. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds.) EKAW 2004. LNCS (LNAI), vol. 3257, pp. 116–131. Springer, Heidelberg (2004)Google Scholar
  13. 13.
    Hanneman, R., Riddle, M.: Introduction to social network methods (2006), http://faculty.ucr.edu/~hanneman/nettext/
  14. 14.
    Hatala, J.P.: Social Network Analysis in Human Resources Development: A New Methodology. Human Resource Development Review 5(1), 45–71 (2006)CrossRefGoogle Scholar
  15. 15.
    Katz, L.: A new status derived from sociometrics analysis. Psychometrica 18, 39–43 (1953)zbMATHCrossRefGoogle Scholar
  16. 16.
    Kazienko, P., Adamski, M.: AdROSA - Adaptive Personalization of Web Advertising. Information Sciences 11, 2269–2295 (2007)CrossRefGoogle Scholar
  17. 17.
    Kazienko, P., Musiał, K.: Recommendation Framework for Online Social Networks. In: AWIC 2006. Studies in Computational Intelligence, vol. 23, pp. 111–120. Springer, Heidelberg (2006)Google Scholar
  18. 18.
    Kazienko, P., Musiał, K.: On Utilizing Social Networks to Discover Representatives of Human Communities. International Journal of Intelligent Information and Database Systems (to appear, 2007)Google Scholar
  19. 19.
    Kazienko, P., Musiał, K.: Social Position of Individuals in Virtual Social Networks (to appear, 2008)Google Scholar
  20. 20.
    Priebey, C.E., Conroy, J.M., Marchette, D.J., Park, Y.: Scan Statistics on Enron Graphs. Computational & Mathematical Organization Theory 11, 229–247 (2005)CrossRefGoogle Scholar
  21. 21.
    Rana, O.F., Hinze, A.: Trust and reputation in dynamic scientific communities. IEEE Distributed Systems Online 5(1) (2004)Google Scholar
  22. 22.
    Shetty, J., Adibi, J.: Discovering Important Nodes through Graph Entropy The Case of Enron Email Databases. In: 3rd International Workshop on Link Discovery, pp. 74–81. ACM Press, New York (2005)CrossRefGoogle Scholar
  23. 23.
    Valverde, S., Theraulaz, G., Gautrais, J., Fourcassie, V., Sole, R.V.: Self-organization patterns in wasp and open source communities. IEEE Intelligent Systems 21(2), 36–40 (2006)CrossRefGoogle Scholar
  24. 24.
    Wasserman, S., Faust, K.: Social network analysis: Methods and applications. Cambridge University Press, New York (1994)Google Scholar
  25. 25.
    Wellman, B., Salaff, J.: Computer Networks as Social Networks: Collaborative Work, Telework, and Virtual Community. Annual Review of Sociology 22, 213–238 (1996)CrossRefGoogle Scholar
  26. 26.
    Yang, W.S., Dia, J.B., Cheng, H.C., Lin, H.T.: Mining Social Networks for Targeted Advertising. In: HICSS 2006, Track 6, p. 137a. IEEE Computer Society, Los Alamitos (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Przemysıaw Kazienko
    • 1
  • Katarzyna Musiał
    • 1
  1. 1.Institute of Applied InformaticsWrocław University of TechnologyPoland

Personalised recommendations