IDEAS home Printed from https://ideas.repec.org/a/wly/complx/v2022y2022i1n1016692.html

The Public Opinion Evolution under Group Interaction in Different Information Features

Author

Listed:
  • Jing Wei
  • Yuguang Jia
  • Yaozeng Zhang
  • Hengmin Zhu
  • Weidong Huang

Abstract

Before expressing opinions, most people usually consider the standpoint of their friends nearby to avoid being isolated, which may lead to the herding effect. The words of celebrities in social networks usually attract public attention and affect the opinion evolution in the entire network. This process also causes the similar status quo. In this study, we find that the key figures play the guiding roles in public opinions who undertake the group pressure from information amount. Therefore, we build the cost function on opinion changes to study opinion evolution rules for public persons based on the spreading scope of information and information amount. Simulation analysis reveals that the information amount held by agents will affect the converging speed of public opinions, while enhancing the ability of key nodes may no more effective in guiding public opinion.

Suggested Citation

  • 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).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:1016692
    DOI: 10.1155/2022/1016692
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2022/1016692
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/1016692?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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).

    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. 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.
    2. Ding, Fei & Liu, Yun & Shen, Bo & Si, Xia-Meng, 2010. "An evolutionary game theory model of binary opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1745-1752.
    3. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    4. Shang, Lihui & Zhao, Mingming & Ai, Jun & Su, Zhan, 2021. "Opinion evolution in the Sznajd model on interdependent chains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    5. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.
    6. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    7. Song, Xiao & Shi, Wen & Tan, Gary & Ma, Yaofei, 2015. "Multi-level tolerance opinion dynamics in military command and control networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 322-332.
    8. Song, Xiao & Zhang, Shaoyun & Qian, Lidong, 2013. "Opinion dynamics in networked command and control organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5206-5217.
    9. Agnieszka Kowalska-Styczeń & Krzysztof Malarz, 2020. "Noise induced unanimity and disorder in opinion formation," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-22, July.
    10. C.R. Martins, André, 2014. "Discrete opinion models as a limit case of the CODA model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 352-357.
    11. Fan, Kangqi & Pedrycz, Witold, 2015. "Emergence and spread of extremist opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 87-97.
    12. Francisco J. León-Medina & Jordi Tena-Sánchez & Francisco J. Miguel, 2020. "Fakers becoming believers: how opinion dynamics are shaped by preference falsification, impression management and coherence heuristics," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 385-412, April.
    13. Lu, Xi & Mo, Hongming & Deng, Yong, 2015. "An evidential opinion dynamics model based on heterogeneous social influential power," Chaos, Solitons & Fractals, Elsevier, vol. 73(C), pages 98-107.
    14. Dimitris Tsintsaris & Milan Tsompanoglou & Evangelos Ioannidis, 2024. "Dynamics of Social Influence and Knowledge in Networks: Sociophysics Models and Applications in Social Trading, Behavioral Finance and Business," Mathematics, MDPI, vol. 12(8), pages 1-27, April.
    15. Hang-Hyun Jo & Jeoung-Yoo Kim, 2012. "Competitive Targeted Marketing," ISER Discussion Paper 0834, Institute of Social and Economic Research, The University of Osaka.
    16. Guzmán-Vargas, L. & Hernández-Pérez, R., 2006. "Small-world topology and memory effects on decision time in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(2), pages 326-332.
    17. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    18. Simões, Tiago S.A.N. & Coniglio, Antonio & Herrmann, Hans J. & de Arcangelis, Lucilla, 2024. "Modeling public opinion control by a charismatic leader," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    19. Si, Xia-Meng & Wang, Wen-Dong & Ma, Yan, 2016. "Role of propagation thresholds in sentiment-based model of opinion evolution with information diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 549-559.
    20. Karataieva, Tatiana & Koshmanenko, Volodymyr & Krawczyk, Małgorzata J. & Kułakowski, Krzysztof, 2019. "Mean field model of a game for power," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 535-547.

    More about this item

    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:wly:complx:v:2022:y:2022:i:1:n:1016692. 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: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/8503 .

    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.