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The Roles of Environmental Noises and Opinion Leaders in Emergency

  • Yiyi Zhao
  • Yi Peng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

This paper proposes a dominant-submissive agent model on bounded confidence opinion dynamics under an emergency environment. In the proposed model, environmental noises and opinion leaders are involved in the collective opinion formation. A series of computer simulations demonstrate that environmental noises have a great impact on the collective opinion evolution. The interactions among individuals are strengthened as the variances of the environmental noises increase, and then a global group behavior emerge with a higher probability. On the other hand, the influence of opinion leaders on the collective opinion dynamics is limited. Firstly, when the fraction of opinion leaders is fixed in the social network, the number of agents following the opinion leaders decreases as the variance of the environmental noise exceeds a certain threshold. Secondly, the number of agents following the opinion leaders does not change obviously as the fraction of opinion leaders increases under a constant noisy environment.

Keywords

Environmental noises Opinion leaders Emergency Opinion propagation Bounded confidence 

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References

  1. 1.
    Boccalettl, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.-U.: Complex networks: structure and dynamics. Physics Reports 424, 175–308 (2006)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Castellano, C., Vilone, D., Vespignani, A.: Incomplete ordering of the voter model on small-world networks. Europhysics Letters 63(1), 153–158 (2003)CrossRefGoogle Scholar
  3. 3.
    Bartolozzi, M., Leinweber, B., Thomas, A.W.: Stochastic Opinion Formation in Scale-Free Networks. Physical Review E 72, 046113 (2005)Google Scholar
  4. 4.
    Sood, V., Redner, S.: Voter Model on Heterogeneous Graphs. Phys. Rev. Lett. 94, 178701 (2005)CrossRefGoogle Scholar
  5. 5.
    Lambiotte, R., Ausloos, M., Holyst, J.: Majority Model on a network with communities. Phys. Rev. E 75, 030101 (2007)Google Scholar
  6. 6.
    Gabbay, M.: The effects of nonlinear interactions and network structure in small group opinion dynamics. Physica A: Statistical Mechanics and its Applications 378(1), 118–126 (2007)CrossRefGoogle Scholar
  7. 7.
    Galam, S.: Heterogeneous beliefs, segregation, and extremism in the making of public opinions. Phys. Rev. E 71, 046123 (2005)Google Scholar
  8. 8.
    Deffuant, G., Amblard, F., Weisbuch, G., Faure, T.: How can extremism prevail? A study based on the relative agreement interaction model. Journal of Artificial Societies and Social Simulation 5(4), 1–10 (2002)Google Scholar
  9. 9.
    Couzin, I.D., Krause, J., Franks, N.R., Levin, S.A.: Effective leadership and decision-making in animal groups on the move. Nature 433(2), 513–516 (2005)CrossRefGoogle Scholar
  10. 10.
    Valente, T.W., Pumpuang, P.: Identifying Opinion Leaders to Promote Behavior Change. Health Education & Behavior 34(6), 881–896 (2006)CrossRefGoogle Scholar
  11. 11.
    Afshar, M., Asadpour, M.: Opinion Formation by Informed Agents. Journal of Artificial Societies and Social Simulation 13, 5 (2010)Google Scholar
  12. 12.
    Deffuant, G., Neau, D., Amblard, F., Weisbuch, G.: Mixing beliefs among interacting agents. Adv. Complex Sys. 3, 87–98 (2000)CrossRefGoogle Scholar
  13. 13.
    Krause, U.: A discrete nonlinear and non-autonomous model of consensus formation. In: Proc. Commun. Difference Equations, pp. 227–236 (2000)Google Scholar
  14. 14.
    Hegselmann, R., Krause, U.: Opinion dynamics and bounded confidence: models, analysis and simulation. Jr. of Art. Soc. and Social Simulation 5, 1–33 (2002)Google Scholar
  15. 15.
    Lorenz, J.: Continuous opinion dynamics under bounded confidence: a survey. Int. Journal of Modern Physics C 18, 1819–1838 (2007)CrossRefzbMATHGoogle Scholar
  16. 16.
    Lorenz, J.: Consensus strikes back in the Hegselmann-Krause model of continuous opinion dynamics under bounded confidence. Journal of Artificial Societies and Social Simulation 9, 8 (2006)Google Scholar
  17. 17.
    Lorenz, J.: Heterogeneous bounds of confidence: Meet, discuss and find consensus! Complexity 4, 43–52 (2010)MathSciNetGoogle Scholar
  18. 18.
    Kou, G., Zhao, Y.Y., Peng, Y., Shi, Y.: Multi-level opinion dynamics under bounded confidence. PLoS One 7(9), e43507 (2012), doi:10.1371/journal.pone.0043507Google Scholar
  19. 19.
    Peng, Y., Kou, G., Shi, Y., Chen, Z.: A Descriptive Framework for the Field of Data Mining and Knowledge Discovery. International Journal of Information Technology & Decision Making 7(4), 639–682 (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Yiyi Zhao
    • 1
  • Yi Peng
    • 1
  1. 1.School of Management and EconomicsUniversity of Electronic Science and Technology of ChinaChengduChina

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