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Social networks, mass media and public opinions

Author

Listed:
  • Haibo Hu

    (East China University of Science and Technology)

  • Jonathan J. H. Zhu

    (City University of Hong Kong)

Abstract

Our opinions and ideas are shaped by what our friends said and what we read or watched on mass media. In this paper, we propose a concise and analyzable model to study the effects of mass media modeled as an applied external field, and social networks on public opinions based on the multi-state voter model, and a tuned parameter can control the relative intensity of the effects of mass media and social networks. We consider a generalized scenario where there exist committed or stubborn agents in the networks whose opinions are not affected by their friends or mass media. We find that the fraction of each opinion will converge to a value which only relates to the fractions and degrees of stubborn agents, and the relative intensity between media and network effects. The final agents with media opinion, except the stubborn agents, also include the increment produced by the internal impact of social networks and that caused by the external impact of media. Interestingly the second increment is composed of two parts, one is from the media effect when there are no interactions between agents and the other is from the influence of media on agent opinions caused by social network structure. That is the interactions among agents within social networks can amplify media influence. Finally we also discuss several extensions to the dynamics model which consider more realistic scenarios.

Suggested Citation

  • Haibo Hu & Jonathan J. H. Zhu, 2017. "Social networks, mass media and public opinions," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 393-411, July.
  • Handle: RePEc:spr:jeicoo:v:12:y:2017:i:2:d:10.1007_s11403-015-0170-8
    DOI: 10.1007/s11403-015-0170-8
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    Cited by:

    1. Zhongtian Chen & Hanlin Lan, 2021. "Dynamics of Public Opinion: Diverse Media and Audiences’ Choices," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(2), pages 1-8.
    2. Hüseyin İkizler, 2019. "Contagion of network products in small-world networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 789-809, December.
    3. Hai-Bo Hu & Cang-Hai Li & Qing-Ying Miao, 2017. "Opinion Diffusion On Multilayer Social Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(06n07), pages 1-25, September.
    4. Markus Brede, 2019. "How Does Active Participation Affect Consensus: Adaptive Network Model of Opinion Dynamics and Influence Maximizing Rewiring," Complexity, Hindawi, vol. 2019, pages 1-16, June.
    5. Mahmoodi, K. & Grigolini, P. & West, B.J., 2018. "On social sensitivity to either zealot or independent minorities," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 185-190.
    6. Jia, Nan & Ding, Li & Liu, Yu-Jing & Hu, Ping, 2018. "Global stability and optimal control of epidemic spreading on multiplex networks with nonlinear mutual interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 93-105.
    7. Mine Halis & Duygu Yildirim, 2022. "The effect of perceived social support and life orientation on anxiety caused by online education in Covid 19 conditions," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(4), pages 310-322, June.
    8. Mitja Steinbacher & Matjaž Steinbacher & Clemens Knoppe, 2024. "Opinion Dynamics with Preference Matching: How the Desire to Meet Facilitates Opinion Exchange," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 735-768, August.

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    More about this item

    Keywords

    Social network; Opinion dynamics; Mass media; Multi-agent model;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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