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Heirarchy of Communities in Dynamic Social Network

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

Discovering the hierarchy of organizational structure can unveil significant patterns that can help in network analysis. In this paper, we used Enron email data which is well-known benchmarked data set for this sort of research domain. We derive a hierarchical structure of organization by calculating the individual score of each person based on their frequency of communication via email using page rank algorithm. After that, a communication graph is plotted that shows power of each individual among themselves. Experimental results showed that this approach was very helpful in identifying primal persons and their persistent links with others over the period of months.

Keywords

Dynamic social network analysis Social network analysis Hierarchal structure. 

References

  1. 1.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods Application. Cambridge University Press, New York (1994)Google Scholar
  2. 2.
    Wellman, B.: Computer networks as social networks. Sci. Mag. 293, 2031–2034 (2001)Google Scholar
  3. 3.
    Robert, A.H., Riddle, M.: Introduction to Social Network Methods. University of California, Riverside (published in digital form http://faculty.ucr.edu/~hanneman/) (2005)
  4. 4.
    Kretzschmar, M., Morris, M.: Measures of concurrency innetworks and the spread of infectious disease. Math. Biosci. 133, 165–195 (1996)CrossRefMATHGoogle Scholar
  5. 5.
    Baumes, J., Goldberg, M., Magdon-Ismail, M., Wallace. W.: Discovering hidden groups in communication networks. In: Proceedings of the 2nd NSF/NIJ Symposium on Intelligence and Security Informatics (2004)Google Scholar
  6. 6.
    Tyler, J., Wilkinson, D., Huberman, B.: Email asspectroscopy: Automated discovery of community structure within organizations. In: Proceedings of the 1st International Conference on Communities and Technologies (2003)Google Scholar
  7. 7.
    Baumes, J., Goldberg, M., Magdon-Ismail, M., Wallace, W.: Discovering hidden groups in communication networks. In: Proceedings 2nd NSF/NIJ Symposium on Intelligence and Security Informatics (2004)Google Scholar
  8. 8.
    Berger-Wolf, T.Y., Saia, J.: A framework for analysis of dynamic social networks. In: Proceedings of the KDD’06, pp. 523–528 (2006)Google Scholar
  9. 9.
    Moitra, A.: Approximation algorithms for multicommoditytype problems with guarantees independent of the graph size. In: Proceedings of the FOCS, pp. 3–12 (2009)Google Scholar
  10. 10.
    Santo, F., Castellano, C.: Community structure in graphs, chapter of Springer’s Encyclopedia of Complexity and System Science (2008)Google Scholar
  11. 11.
    Chekuri, C., Goldberg, A., Karger, D., Levin, M., Stein, C.: Experimental study of minimum cut algorithms. In: Proceedings of the 8th SAIM Symposium on Discreet Algorithm, pp. 324–333 (1997)Google Scholar
  12. 12.
    Andrew, Y., Wu., et al.: Mining scale-free networks using geodesic clustering. In: Proceedings of the KDD’04, pp. 719–724 (2004)Google Scholar
  13. 13.
    Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004)Google Scholar
  14. 14.
    Newman, M.E.J.: Modularity and community structure in networks. PNAS 103(23), 8577–8582 (2006)Google Scholar
  15. 15.
    Zhou, D., Councill, I., Zha, H., Lee Giles, C.: Discovering temporal communities from social network documents. In: Proceedings of the ICDM’07, pp. 745–750 (2007)Google Scholar
  16. 16.
    Tantipathananandh, C., Berger-Wolf, T., David Kempe, A.: Framework for community identification in dynamic social networks. In: Proceedings of the KDD’07, pp. 717–726 (2007)Google Scholar
  17. 17.
    The original dataset can be downloaded from William Cohen’s web page http://www-2.cs.cmu.edu/~enron/

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Robotics and AI LabIndian Institute of Information TechnologyAllahabadIndia

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