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Stable Statistics of the Blogograph

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Protecting Persons While Protecting the People (ISIPS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5661))

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Abstract

The primary focus of this paper is to describe stable statistics of the blogosphere’s evolution which convey information on the social network’s dynamics. In this paper, we present a number of non-trivial statistics that are surprisingly stable and thus can be used as benchmarks to diagnose phase-transitions in the network. We believe that stable statistics can be used to identify anomalous behavior at all levels: that of a node, of a local community, or of the entire network itself. Any substantial change in those stable statistics must alert the researchers and analysts to the need for further investigation. Furthermore, the usage of these or similar statistics that are based solely on the communication dynamics and not on the communication content, allows one to diagnose anomalous behavior with minimal intrusion of privacy.

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References

  1. Barabási, A., Jeong, J., Nëda, Z., Ravasz, E., Shubert, A., Vicsek, T.: Evolution of the social network of scientific collaborations. Physica A311, 590–614 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  2. Baumes, J., Goldberg, M.K., Magdon-Ismail, M.: Efficient identification of overlapping communities. In: Kantor, P., Muresan, G., Roberts, F., Zeng, D.D., Wang, F.-Y., Chen, H., Merkle, R.C. (eds.) ISI 2005. LNCS, vol. 3495, pp. 27–36. Springer, Heidelberg (2005)

    Google Scholar 

  3. Clauset, A., Shalizi, C.R., Newman, M.E.J.: Power-law distributions in empirical data. SIAM Review (to appear, 2009)

    Google Scholar 

  4. Goh, K.-I., Eom, Y.-H., Jeong, H., Kahng, B., Kim, D.: Structure and evolution of online social relationships: Heterogeneity in unrestricted discussions. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics) 73(6), 066123 (2006)

    Google Scholar 

  5. Kossinets, G., Watts, D.J.: Empirical analysis of an evolving social network. Science 311, 88–90 (2006)

    Article  MathSciNet  Google Scholar 

  6. Newman, M.E.J.: The structure of scientific collaboration networks. Proc. Natl. Acad. Sci. USA 98, 404 (2001)

    Article  MATH  MathSciNet  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Goldberg, M., Magdon-Ismail, M., Kelley, S., Mertsalov, K. (2009). Stable Statistics of the Blogograph. In: Gal, C.S., Kantor, P.B., Lesk, M.E. (eds) Protecting Persons While Protecting the People. ISIPS 2008. Lecture Notes in Computer Science, vol 5661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10233-2_10

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  • DOI: https://doi.org/10.1007/978-3-642-10233-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10232-5

  • Online ISBN: 978-3-642-10233-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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