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Clusters and the entropy in opinion dynamics on complex networks

Author

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  • Han, Wenchen
  • Feng, Yuee
  • Qian, Xiaolan
  • Yang, Qihui
  • Huang, Changwei

Abstract

In this work, we investigate a heterogeneous population in the modified Hegselmann–Krause opinion model on complex networks. We introduce the Shannon information entropy about all relative opinion clusters to characterize the cluster profile in the final configuration. Independent of network structures, there exists the optimal stubbornness of one subpopulation for the largest number of clusters and the highest entropy. Besides, there is the optimal bounded confidence (or subpopulation ratio) of one subpopulation for the smallest number of clusters and the lowest entropy. However, network structures affect cluster profiles indeed. A large average degree favors consensus for making different networks more similar with complete graphs. The network size has limited impact on cluster profiles of heterogeneous populations on scale-free networks but has significant effects upon those on small-world networks.

Suggested Citation

  • Han, Wenchen & Feng, Yuee & Qian, Xiaolan & Yang, Qihui & Huang, Changwei, 2020. "Clusters and the entropy in opinion dynamics on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    • Handle: RePEc:eee:phsmap:v:559:y:2020:i:c:s0378437120305380
    DOI: 10.1016/j.physa.2020.125033
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    References listed on IDEAS

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    1. Gandica, Yérali & del Castillo-Mussot, Marcelo & Vázquez, Gerardo J. & Rojas, Sergio, 2010. "Continuous opinion model in small-world directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5864-5870.
    2. Xi Chen & Shen Zhao & Wei Li, 2019. "Opinion Dynamics Model Based on Cognitive Styles: Field-Dependence and Field-Independence," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    3. Jalili, Mahdi, 2013. "Social power and opinion formation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 959-966.
    4. Wang, Shaoli & Rong, Libin & Wu, Jianhong, 2016. "Bistability and multistability in opinion dynamics models," Applied Mathematics and Computation, Elsevier, vol. 289(C), pages 388-395.
    5. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    6. AskariSichani, Omid & Jalili, Mahdi, 2015. "Influence maximization of informed agents in social networks," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 229-239.
    7. Pineda, M. & Buendía, G.M., 2015. "Mass media and heterogeneous bounds of confidence in continuous opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 73-84.
    8. Fu, Guiyuan & Zhang, Weidong & Li, Zhijun, 2015. "Opinion dynamics of modified Hegselmann–Krause model in a group-based population with heterogeneous bounded confidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 558-565.
    9. Han, Wenchen & Huang, Changwei & Yang, Junzhong, 2019. "Opinion clusters in a modified Hegselmann–Krause model with heterogeneous bounded confidences and stubbornness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    10. Jan Lorenz, 2007. "Continuous Opinion Dynamics Under Bounded Confidence: A Survey," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(12), pages 1819-1838.
    11. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    12. Guillaume Deffuant & David Neau & Frederic Amblard & Gérard Weisbuch, 2000. "Mixing beliefs among interacting agents," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 87-98.
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    Cited by:

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    3. Huang, Changwei & Hou, Yongzhao & Han, Wenchen, 2023. "Coevolution of consensus and cooperation in evolutionary Hegselmann–Krause dilemma with the cooperation cost," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    4. Gomes, P.F. & Fernandes, H.A. & Costa, A.A., 2022. "Topological transition in a coupled dynamics in random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

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