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The strength of the minority

Author

Listed:
  • Huang, Gan
  • Cao, Jinde
  • Wang, Guanjun
  • Qu, Yuzhong

Abstract

In this paper, we focus on the problem of opinion formation by introducing a simple model with a certain community structure. To understand the strength of the community, we took a particular interest in a special problem of how the opinion of a small but cohesive community could persist or even be finally accepted by the majority of the society. Both simulation and analysis has been done in the absence and presence of noise. In the noiseless environment, assuming the population of the community is fixed, if the cohesion of the community reaches a certain level, then the phase transition will occur in the evolution process that the community will never be assimilated even if it can assimilate the other nodes in the network, which depends on the population of the community. On the other hand, in the presence of noise, the process of opinion formation seems more complex that two transition behaviors occur outside and inside the community as the noise level increases. And the outcomes of the evolution may be completely opposite under different noise conditions.

Suggested Citation

  • Huang, Gan & Cao, Jinde & Wang, Guanjun & Qu, Yuzhong, 2008. "The strength of the minority," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4665-4672.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:18:p:4665-4672
    DOI: 10.1016/j.physa.2008.03.033
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    References listed on IDEAS

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    1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
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    Cited by:

    1. Ma, Jing & Li, Dandan & Tian, Zihao, 2016. "Rumor spreading in online social networks by considering the bipolar social reinforcement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 108-115.
    2. Cheng, Chun & Luo, Yun & Yu, Changbin, 2020. "Dynamic mechanism of social bots interfering with public opinion in network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    3. AskariSichani, Omid & Jalili, Mahdi, 2015. "Influence maximization of informed agents in social networks," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 229-239.
    4. Balankin, Alexander S. & Martínez Cruz, Miguel Ángel & Martínez, Alfredo Trejo, 2011. "Effect of initial concentration and spatial heterogeneity of active agent distribution on opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3876-3887.
    5. Pires, Marcelo A. & Crokidakis, Nuno, 2017. "Dynamics of epidemic spreading with vaccination: Impact of social pressure and engagement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 167-179.
    6. Gaudiano, Marcos E. & Revelli, Jorge A., 2019. "Spontaneous emergence of a third position in an opinion formation model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 501-511.

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