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Emergence of Influential Spreaders in Modified Rumor Models

Abstract

The burst in the use of online social networks over the last decade has provided evidence that current rumor spreading models miss some fundamental ingredients in order to reproduce how information is disseminated. In particular, recent literature has revealed that these models fail to reproduce the fact that some nodes in a network have an influential role when it comes to spread a piece of information. In this work, we introduce two mechanisms with the aim of filling the gap between theoretical and experimental results. The first model introduces the assumption that spreaders are not always active whereas the second model considers the possibility that an ignorant is not interested in spreading the rumor. In both cases, results from numerical simulations show a higher adhesion to real data than classical rumor spreading models. Our results shed some light on the mechanisms underlying the spreading of information and ideas in large social systems and pave the way for more realistic diffusion models.

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References

  1. 1.

    Bakshy, E., Rosenn, I., Marlow, C., Adamic, L.A.: The role of social networks in information diffusion. In: WWW’12, p. 519 (2012)

  2. 2.

    Barabasi, A.: The origin of bursts and heavy tails in human dynamics. Nature 435, 207–211 (2005)

    ADS  Article  Google Scholar 

  3. 3.

    Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.: Complex networks: structure and dynamics. Phys. Rep. 424, 175–308 (2006)

    MathSciNet  ADS  Article  Google Scholar 

  4. 4.

    Borge-Holthoefer, J., Moreno, Y.: Absence of influential spreaders in rumor dynamics. Phys. Rev. E 85, 026116 (2012)

    ADS  Article  Google Scholar 

  5. 5.

    Borge-Holthoefer, J., Rivero, A., Moreno, Y.: Locating privileged spreaders on an online social network. Phys. Rev. E 85, 066123 (2012)

    ADS  Article  Google Scholar 

  6. 6.

    Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Rev. Mod. Phys. 81, 591 (2009)

    ADS  Article  Google Scholar 

  7. 7.

    Castellano, C., Pastor-Satorras, R.: Competing activation mechanisms in epidemics on networks. Sci. Rep. 2, 371 (2012)

    Article  Google Scholar 

  8. 8.

    Cosley, D., Huttenlocher, D., Kleinberg, J., Lan, X., Suri, S.: Sequential influence models in social networks. In: ICWSM’10, p. 26 (2010)

  9. 9.

    Daley, D.J., Kendal, D.G.: Stochastic rumours. J. Inst. Math. Appl. 1, 42 (1965)

    MathSciNet  Article  Google Scholar 

  10. 10.

    Daley, D.J., Gani, J.: Epidemic Modelling. Cambridge University Press, Cambridge (2000)

    Google Scholar 

  11. 11.

    Dietz, K.: Epidemics and rumours: a survey. J. R. Stat. Soc. A, General 130, 505 (1967)

    MathSciNet  Article  Google Scholar 

  12. 12.

    Galam, S.: Modeling rumors: the no plane Pentagon French hoax case. Physica A 320, 571 (2003)

    MathSciNet  ADS  MATH  Article  Google Scholar 

  13. 13.

    Goffman, W., Newill, V.A.: Generalization of epidemic theory—an application to the transmission of ideas. Nature 204, 225 (1964)

    ADS  Article  Google Scholar 

  14. 14.

    Gonçalves, B., Ramasco, J.J.: Human dynamics revealed through web analytics. Phys. Rev. E 78, 026123 (2008)

    ADS  Article  Google Scholar 

  15. 15.

    González-Bailón, S., Borge-Holthoefer, J., Rivero, A., Moreno, Y.: The dynamics of protest recruitment through an online network. Sci. Rep. 1, 197 (2011)

    Google Scholar 

  16. 16.

    Kimmel, A.J.: Rumors and rumor control. J. Behav. Finance 5, 134 (2004)

    Article  Google Scholar 

  17. 17.

    Kitsak, M., Gallos, L., Havlin, S., Liljeros, F., Muchnik, L., Stanley, H., Makse, H.: Identification of influential spreaders in complex networks. Nat. Phys. 6, 888 (2010)

    Article  Google Scholar 

  18. 18.

    Klemm, K., Serrano, M., Eguiluz, V., Miguel, M.: A measure of individual role in collective dynamics: spreading at criticality. Sci. Rep. 2, 292 (2012)

    Article  Google Scholar 

  19. 19.

    Kosfeld, M.: Rumours and markets. J. Math. Econ. 41, 646 (2005)

    MathSciNet  MATH  Article  Google Scholar 

  20. 20.

    Lloyd-Smith, J.O., Schreiber, S.J., Kopp, P.E., Getz, W.M.: Superspreading and the effect of individual variation on disease emergence. Nature 438, 355 (2005). http://www.nature.com/nature/journal/v438/n7066/full/nature04153.html

    ADS  Article  Google Scholar 

  21. 21.

    Moreno, Y., Nekovee, M., Vespignani, A.: Efficiency and reliability of epidemic data dissemination in complex networks. Phys. Rev. E 69, 055101 (2004)

    ADS  Article  Google Scholar 

  22. 22.

    Nekovee, M., Moreno, Y., Bianconi, G., Marsili, M.: Theory of rumour spreading in complex social networks. Physica A 374, 457–470 (2007)

    ADS  Article  Google Scholar 

  23. 23.

    Perra, N., Gonçalves, B., Pastor-Satorras, R., Vespignani, A.: Activity driven modeling of dynamic networks. Sci. Rep. 2, 469 (2012)

    Article  Google Scholar 

  24. 24.

    Rogers, E.M.: Diffusion of Innovations, 5th edn. Free Press, New York (2003)

    Google Scholar 

  25. 25.

    Vazquez, A., Racz, B., Lukacs, A., Barabasi, A.: Impact of non-Poissonian activity patterns on spreading processes. Phys. Rev. Lett. 98, 158702 (2007)

    ADS  Article  Google Scholar 

  26. 26.

    Watts, D.J., Dodds, P.S.: Influentials, networks, and public opinion formation. J. Consum. Res. 34, 441 (2007)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank A. Rivero for the help in collecting Twitter data and useful discussions. This work has been partially supported by MICINN through Grants No. FIS2008-01240, FIS2009-13364-C02-01 and FIS2011-25167, and by the Government of Aragón (DGA) through a grant to FENOL group.

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Correspondence to Yamir Moreno.

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Borge-Holthoefer, J., Meloni, S., Gonçalves, B. et al. Emergence of Influential Spreaders in Modified Rumor Models. J Stat Phys 151, 383–393 (2013). https://doi.org/10.1007/s10955-012-0595-6

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Keywords

  • Rumor spreading
  • Online social networks
  • Human activity patterns