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From classical to modern opinion dynamics

Author

Listed:
  • Hossein Noorazar

    (Washington State University, Pullman, Washington 99164-3113, USA)

  • Kevin R. Vixie

    (Department of Mathematics and Statistics, Washington State University, Pullman, Washington 99164-3113, USA)

  • Arghavan Talebanpour

    (Department of Mechanical and Material Engineering, Washington State University, Pullman, Washington 99164-3113, USA)

  • Yunfeng Hu

    (Washington State University, Pullman, Washington 99164-3113, USA)

Abstract

In this age of Facebook, Instagram, and Twitter, there is rapidly growing interest in understanding network-enabled opinion dynamics in large groups of autonomous agents. The phenomena of opinion polarization, the spread of propaganda and fake news, and the manipulation of sentiment is of interest to large numbers of organizations and people. Whether it is the more nefarious players such as foreign governments that are attempting to sway elections or it is more open and above board, such as researchers who want to make large groups of people aware of helpful innovations, what is at stake is often significant.In this paper, we review opinion dynamics including the extensions of many classical models as well as some new models that deepen understanding. For example, we look at models that track the evolution of an individual’s power, that include noise, and that feature sequentially dependent topics, to name a few.While the first papers studying opinion dynamics appeared over 60 years ago, there is still a great deal of room for innovation and exploration. We believe that the political climate and the extraordinary (even unprecedented) events in the sphere of politics in the last few years will inspire new interest and new ideas.It is our aim to help those interested researchers understand what has already been explored in a significant portion of the field of opinion dynamics. We believe that in doing this, it will become clear that there is still much to be done.

Suggested Citation

  • Hossein Noorazar & Kevin R. Vixie & Arghavan Talebanpour & Yunfeng Hu, 2020. "From classical to modern opinion dynamics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(07), pages 1-60, July.
    • Handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:07:n:s0129183120501016
    DOI: 10.1142/S0129183120501016
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    Citations

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    Cited by:

    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. Muslim, Roni & NQZ, Rinto Anugraha & Khalif, Muhammad Ardhi, 2024. "Mass media and its impact on opinion dynamics of the nonlinear q-voter model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    4. Vaidya, Tushar & Chotibut, Thiparat & Piliouras, Georgios, 2021. "Broken detailed balance and non-equilibrium dynamics in noisy social learning models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    5. Paul Bouchaud, 2024. "Skewed perspectives: examining the influence of engagement maximization on content diversity in social media feeds," Journal of Computational Social Science, Springer, vol. 7(1), pages 721-739, April.
    6. 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).

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