IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v674y2025ics0378437125003759.html

On demonstrating liberating effect in complex social networks: Modeling multiple pressure-coping strategies

Author

Listed:
  • Peng, Yuan
  • Zhao, Yiyi
  • Dong, Jianglin
  • Hu, Jiangping

Abstract

This paper introduces a novel opinion dynamics model, termed the Multiple Pressure-Coping Strategies (MPCS) mode, to investigate the opinion evolution in social networks under group pressure. The model extends the Expressed and Private Opinions (EPO) model based on the Hegselmann–Krause (HK) framework. It includes a quantifiable pressure function, heterogeneous confidence levels, a two-stage liberating effect mechanism, and a dynamic evolution of the network structure. Simulations conducted on two artificial networks and a real network demonstrate that the MPCS model is more effective in achieving consensus under conditions of initial low confidence levels and significant group pressure compared to the classic HK model. We find the critical role of initial confidence levels in consensus time. Our research highlights the impact of different pressure-coping strategies on opinion evolution. In the early iterations of evolution, agents reduce group pressure by increasing confidence levels and updating the network; in the later iterations, the liberating effect becomes pivotal in shaping opinion dynamics. The role of the liberating effect is reflected in its ability to further reduce the pressure on high-pressure nodes within the group and optimize the network structure, thereby facilitating the achievement of group consensus.

Suggested Citation

  • Peng, Yuan & Zhao, Yiyi & Dong, Jianglin & Hu, Jiangping, 2025. "On demonstrating liberating effect in complex social networks: Modeling multiple pressure-coping strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 674(C).
  • Handle: RePEc:eee:phsmap:v:674:y:2025:i:c:s0378437125003759
    DOI: 10.1016/j.physa.2025.130723
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125003759
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2025.130723?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Cheng, Chun & Yu, Changbin, 2019. "Opinion dynamics with bounded confidence and group pressure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    2. M. E. J. Newman & D. J. Watts, 1999. "Renormalization Group Analysis of the Small-World Network Model," Working Papers 99-04-029, Santa Fe Institute.
    3. Zhu, Yueying & Jiang, Jian & Li, Wei, 2023. "The critical behavior of Hegselmann–Krause opinion model with smart agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    4. Huang, Changwei & Dai, Qionglin & Han, Wenchen & Feng, Yuee & Cheng, Hongyan & Li, Haihong, 2018. "Effects of heterogeneous convergence rate on consensus in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 428-435.
    5. Jing Wei & Yuguang Jia & Yaozeng Zhang & Hengmin Zhu & Weidong Huang & Peican Zhu, 2022. "The Public Opinion Evolution under Group Interaction in Different Information Features," Complexity, Hindawi, vol. 2022, pages 1-15, May.
    6. Jing Wei & Yuguang Jia & Yaozeng Zhang & Hengmin Zhu & Weidong Huang, 2022. "The Public Opinion Evolution under Group Interaction in Different Information Features," Complexity, John Wiley & Sons, vol. 2022(1).
    7. Xiaoxuan Liu & Changwei Huang & Haihong Li & Qionglin Dai & Junzhong Yang & Wei Zhou, 2021. "The Combination of Pairwise and Group Interactions Promotes Consensus in Opinion Dynamics," Complexity, Hindawi, vol. 2021, pages 1-8, January.
    8. 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.
    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. 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).
    11. Hou, Jian & Li, Wenshan & Jiang, Mingyue, 2021. "Opinion dynamics in modified expressed and private model with bounded confidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ding, Haixin & Xie, Li, 2024. "The applicability of positive information in negative opinion management: An attitude-laden communication perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    2. Han, Wenchen & Gao, Shun & Huang, Changwei & Yang, Junzhong, 2022. "Non-consensus states in circular opinion model with repulsive interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    3. Huang, Changwei & Bian, Huanyu & Han, Wenchen, 2024. "Breaking the symmetry neutralizes the extremization under the repulsion and higher order interactions," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    4. 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).
    5. Wang, Chaoqian, 2021. "Opinion dynamics with bilateral propaganda and unilateral information blockade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    6. Hou, Jian & Li, Wenshan & Jiang, Mingyue, 2021. "Opinion dynamics in modified expressed and private model with bounded confidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    7. Dong Jiang & Qionglin Dai & Haihong Li & Junzhong Yang, 2024. "Opinion dynamics based on social learning theory," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(12), pages 1-9, December.
    8. Cahill, Patrick & Gottwald, Georg A., 2025. "A modified Hegselmann–Krause model for interacting voters and political parties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 665(C).
    9. Song, Xiao & Shi, Wen & Ma, Yaofei & Yang, Chen, 2015. "Impact of informal networks on opinion dynamics in hierarchically formal organization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 916-924.
    10. Luo, Yijun & Huang, Changwei & Han, Wenchen, 2024. "The evolution of cooperation and global synchronization in the evolutionary Kuramoto dilemma combined with the prisoner's dilemma," Applied Mathematics and Computation, Elsevier, vol. 482(C).
    11. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    12. Zhang, Lan & Gao, Shun, 2025. "The impact of environment-based heterogeneous bounded confidence on opinion dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 201(P2).
    13. Yang, Yizhou & Li, Haihong & Gao, Shun & Dai, Qionglin & Yang, Junzhong, 2025. "Interdependent evolutionary dynamics of opinion and strategy on two-layer networks," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    14. Takesue, Hirofumi, 2023. "Relative opinion similarity leads to the emergence of large clusters in opinion formation models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    15. Wang, Chaoqian & Huang, Chaochao, 2022. "Between local and global strategy updating in public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    16. 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).
    17. Li, Zhifang & Chen, Xiaojie, 2026. "Evolutionary dynamics of binary opinions with decision errors on social networks," Applied Mathematics and Computation, Elsevier, vol. 514(C).
    18. Lin, Hui & Gong, Wenying & Nie, Qi & Wu, Lihua & Yuan, Liu & Du, Wen & Jiang, Hao, 2025. "ODEN: The opinion dynamics of events and norms model on social media platforms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 674(C).
    19. Teo Victor Silva & Sebastián Gonçalves & Bruno Requião Cunha, 2024. "Bounded confidence opinion dynamics with Asch-like social conformity in complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(9), pages 1-10, September.
    20. Xianchuan Yang & Yin Ma, 2026. "Beyond conformity: exploring the moderated role of peer effects in shaping business model innovation amid public opinion uncertainty," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 13(1), pages 1-15, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:674:y:2025:i:c:s0378437125003759. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.