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The decentralized flow structure of clickstreams on the web

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Abstract

The browsing behavior of massive web users forms a flow network transporting user’ collective attention between websites. By analyzing the circulation of the collective attention we discover the scaling relationship between the impact of sites and their traffic. We construct three clickstreams networks, whose nodes were websites and edges were formed by the users’ switching between sites. The impact of site i, C i , is measured by the clickstreams controlled by this site in the circulation of clickstreams. We find that C i scales sublinearly with A i , the traffic of site i. Specifically, there existed a relationship C i  ~ A i γ(γ < 1), which implies the decentralized structure of the clickstream circulation.

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References

  1. D. Watts, S. Strogatz, Nature 393, 440 (1998)

    Article  ADS  Google Scholar 

  2. A. Broder et al., Computer networks 33, 309 (2000)

    Article  ADS  Google Scholar 

  3. J. Kleinberg, S. Lawrence, Science 294, 1849 (2001)

    Article  Google Scholar 

  4. J. Kleinberg et al., Nature 406, 845 (2000)

    Article  ADS  Google Scholar 

  5. L. Page, S. Brin, R. Motwani, T. Winograd, The pagerank citation ranking: Bringing order to the web. Technical report, Stanford InfoLab (1999). http://ilpubs.stanford.edu:8090/422/

  6. M. Meiss, B. Gonçalves, J. Ramasco, A. Flammini, F. Menczer, in Proceedings of the 21st ACM conference on Hypertext and hypermedia, ACM, 2010, pp. 229–234

  7. F. Qiu, Z. Liu, J. Cho, in Proceedings International Workshop on the Web and Databases (WebDB), Citeseer 2005, pp. 103–108

  8. A. Chmiel, K. Kowalska, J. Hołyst, Phys. Rev. E 80, 066122 (2009)

    Article  ADS  Google Scholar 

  9. R. White, J. Huang, in Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval, ACM 2010, pp. 587–594

  10. M. Meiss, F. Menczer, S. Fortunato, A. Flammini, A. Vespignani, in Proceedings of the international conference on Web search and web data mining, ACM, 2008, pp. 65–76

  11. B.A. Huberman, P. Pirolli, J. Pitkow, R. Lukose, Science 280, 95 (1998)

    Article  ADS  Google Scholar 

  12. J. Bollen et al., PLoS One 4, e4803 (2009)

    Article  ADS  Google Scholar 

  13. A. Barabási, R. Albert, Science 286, 509 (1999)

    Article  MathSciNet  ADS  Google Scholar 

  14. J. Cho, S. Roy, in Proceedings of the 13th international conference on World Wide Web, ACM, 2004, pp. 20–29

  15. L. Introna, H. Nissenbaum, Computer 33, 54 (2000)

    Article  Google Scholar 

  16. S. Fortunato, A. Flammini, F. Menczer, A. Vespignani, Proc. Natl. Acad. Sci. 103, 12684 (2006)

    Article  ADS  Google Scholar 

  17. J. Brainerd, B. Becker, in Proceedings of the IEEE Symposium on Information Visualization, 2001 (INFOVIS’01), IEEE Computer Society, p. 153

  18. G. Funkhouser, M. McCombs, The Public Opinion Quarterly 35, 107 (1971)

    Article  Google Scholar 

  19. K. Lerman, R. Ghosh, in Proceedings of 4th International Conference on Weblogs and Social Media (ICWSM), 2010

  20. F. Wu, B.A. Huberman, Proc. Natl. Acad. Sci. 104, 17599 (2007)

    Article  ADS  Google Scholar 

  21. C. Cattuto, A. Barrat, A. Baldassarri, G. Schehr, V. Loreto, Proc. Natl. Acad. Sci. 106, 10511 (2009)

    Google Scholar 

  22. F. Wu, D. Wilkinson, B. Huberman, in Computational Science and Engineering, 2009. CSE’09. International Conference on IEEE, 4, 409 (2009)

  23. N. Foti, J. Hughes, D. Rockmore, PloS One 6, e16431 (2011)

    Article  ADS  Google Scholar 

  24. T. Fruchterman, E. Reingold, Software: Practice and experience 21, 1129 (1991)

    Article  Google Scholar 

  25. J. Zhang, L. Guo, J. Theor. Biol. 264, 760 (2010)

    Article  Google Scholar 

  26. M. Barber, Ecological Modelling 5, 193 (1978)

    Article  Google Scholar 

  27. M. Higashi, Ecological Modelling 32, 137 (1986)

    Article  Google Scholar 

  28. D. Garlaschelli, G. Caldarelli, L. Pietronero, Nature 423, 165 (2003)

    Article  ADS  Google Scholar 

  29. D. Warton, I. Wright, D. Falster, M. Westoby, Biol. Rev. 81, 259 (2006)

    Article  Google Scholar 

  30. P. Pirolli, Information foraging theory: Adaptive interaction with information (Oxford University Press, New York, 2007), Vol. 2

  31. M. Higashi, B. Patten, T. Burns, Ecological modelling 66, 1 (1993)

    Article  Google Scholar 

  32. S. Vitali, J. Glattfelder, S. Battiston, PloS One 6, e25995 (2011)

    Article  ADS  Google Scholar 

  33. N. Smirnov, Annal. Math. Stat. 19, 279 (1948)

    Article  MATH  Google Scholar 

  34. A. Clauset, C. Shalizi, M. Newman, Soc. Ind. Appl. Math. Rev. 51, 661 (2009)

    MathSciNet  MATH  Google Scholar 

  35. D. Rosen, E. Purinton, J. Business Res. 57, 787 (2004)

    Article  Google Scholar 

  36. G. Tan, K. Wei, Electron. Commerce Res. Appl. 5, 261 (2007)

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Media and Communication, City University of Hong Kong, Hong Kong, P.R. China

    Lingfei Wu

  2. School of Management, Beijing Normal University, Beijing, 100875, P.R. China

    Jiang Zhang

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  1. Lingfei Wu
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  2. Jiang Zhang
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Correspondence to Jiang Zhang.

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Wu, L., Zhang, J. The decentralized flow structure of clickstreams on the web. Eur. Phys. J. B 86, 266 (2013). https://doi.org/10.1140/epjb/e2013-40132-2

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  • DOI: https://doi.org/10.1140/epjb/e2013-40132-2

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