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ODEN: The opinion dynamics of events and norms model on social media platforms

Author

Listed:
  • Lin, Hui
  • Gong, Wenying
  • Nie, Qi
  • Wu, Lihua
  • Yuan, Liu
  • Du, Wen
  • Jiang, Hao

Abstract

Opinion dynamics are crucial in studying opinion evolution on social media platforms. Real-world events can spark discussions on social media, and the platform characteristics can shape these conversations. However, existing research often neglects these factors. This paper proposes the Opinion Dynamics of Events and Norms (ODEN) model. ODEN incorporates the Hawkes process to quantify the impact of real-world events and a hyperbolic tangent function to represent the social norms on social media platforms. The model accurately captures opinion evolution influenced by the real world, validated by prediction experiments on real datasets. Additionally, we conduct simulation experiments to provide references for intervening in opinion polarization. The research highlights the importance of considering real-world events and social norms in understanding opinion dynamics on social media.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:674:y:2025:i:c:s0378437125004261
    DOI: 10.1016/j.physa.2025.130774
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    References listed on IDEAS

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    1. Zhu, Jiefan & Yao, Yiping & Tang, Wenjie & Zhang, Haoming, 2022. "An agent-based model of opinion dynamics with attitude-hiding behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    2. Botte, Nina & Ryckebusch, Jan & Rocha, Luis E.C., 2022. "Clustering and stubbornness regulate the formation of echo chambers in personalised opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    3. repec:plo:pcbi00:1006749 is not listed on IDEAS
    4. Francesca Giardini & Daniele Vilone, 2021. "Opinion Dynamics and Collective Risk Perception: An Agent-Based Model of Institutional and Media Communication About Disasters," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(1), pages 1-4.
    5. Li, Tingyu & Zhu, Hengmin, 2020. "Effect of the media on the opinion dynamics in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    6. Kiyoshi Kanazawa & Didier Sornette, 2021. "Ubiquitous power law scaling in nonlinear self-excited Hawkes processes," Papers 2102.00242, arXiv.org, revised Oct 2021.
    7. 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.
    8. 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.
    9. Jiang, Hao & Zheng, Yuke & Nie, Qi & Wu, Lihua & Liu, Xiaohan & Du, Wen & Wang, Yingxue & Ye, Dongsheng, 2025. "CIOG: Coupled dynamics of information spreading and opinion evolution through social media groups," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 674(C).
    10. 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).
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