Information Dissemination in Scale-Free Networks: Profusion Versus Scarcity

  • Laurent BrissonEmail author
  • Philippe Collard
  • Martine Collard
  • Erick Stattner
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 689)


The study of information dissemination in social networks is of particular importance in many areas as marketing, politics and security for example. Various strategies are being developed to disseminate information, those aimed at disseminating information widely and those aimed at disseminating information in a more confidential manner to make it scarce. In this paper, we adapt a model dedicated to spreading rumours by word of mouth in a physical space to the context of social networks. We compare two modes of dissemination based on profusion or scarcity and study the impact of the choice of the initial node. The results obtained show to what extent each mode exploits the social network topology and especially the influence of hubs.


  1. 1.
    Albert, R., Barabási, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002).
  2. 2.
    Borge-Holthoefer, J., Meloni, S., Gonçalves, B., Moreno, Y.: Emergence of influential spreaders in modified rumor models. J. Stat. Phys. 151, 383–393 (2013).
  3. 3.
    Cheng, J.J., Liu, Y., Shen, B., Yuan, W.G.: An epidemic model of rumor diffusion in online social networks. Eur. Phys. J. B 86(1), 29 (2013).
  4. 4.
    Chmiel, A., Sienkiewicz, J., Thelwall, M., Paltoglou, G., Buckley, K., Kappas, A., Hołyst, J.A.: Collective emotions online and their influence on community life. PLoS ONE 6(7) (2011).
  5. 5.
    Collard, M., Collard, P., Brisson, L., Stattner, E.: Rumor spreading modeling: profusion versus scarcity. In: ASONAM 2015, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 1547–1554 (2015)Google Scholar
  6. 6.
    Daley, D.J., Kendall, D.G.: Epidemics and rumours. Nature 204(4963), 1118 (1964).
  7. 7.
    Doer, B., Fouz, M., Friedrich, T.: Why rumors spread so quickly in social networks. Commun. ACM 55(6), 70 (2012).
  8. 8.
    Garcia, D., Kappas, A., Küster, D., Schweitzer, F.: The dynamics of emotions in online interaction. R. Soc. Open Sci., 1–26 (2016, to appear).
  9. 9.
    Guadagno, R.E., Rempala, D.M., Murphy, S., Okdie, B.M.: What makes a video go viral? An analysis of emotional contagion and Internet memes. Comput. Hum. Behav. 29(6), 2312–2319 (2013).
  10. 10.
    He, Z., Cai, Z., Wang, X.: Modeling propagation dynamics and developing optimized countermeasures for rumor spreading in online social networks. In: Proceedings of the International Conference on Distributed Computing Systems, July, 2015, pp. 205–214 (2015).
  11. 11.
    Kermack, W.O., McKendrick, A.G.: A contribution to the mathematical theory of epidemics. Proc. R. S. Lond. Ser. A 115, 700–721 (1927)CrossRefzbMATHGoogle Scholar
  12. 12.
    Schweitzer, F., Garcia, D.: An agent-based model of collective emotions in online communities. Eur. Phys, J. B (2008)Google Scholar
  13. 13.
    Xia, Z., Huang, L.: Emergence of social rumor: modeling, analysis, and simulations. Comput. Sci., 90–97 (2007)Google Scholar
  14. 14.
    Zhao, X., Wang, J.: Dynamical model about rumor spreading with medium. Discret. Dyn. Nat. Soc. 2013, 1–9 (2013).

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Laurent Brisson
    • 1
    Email author
  • Philippe Collard
    • 2
  • Martine Collard
    • 3
  • Erick Stattner
    • 3
  1. 1.IMT Atlantique, Lab-STICC, UBLBrestFrance
  2. 2.Université Côte d’Azur, CNRS, I3S, UMR 7271, UNS, Parc ValroseNiceFrance
  3. 3.LAMIA LaboratoryUniversity of the French West IndiesGuadeloupeFrance

Personalised recommendations