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Changing Opinions In A Changing World: A New Perspective In Sociophysics

Author

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  • ALESSANDRO PLUCHINO

    (Dipartimento di Fisica e Astronomia and Infn sezione di Catania, Universitá di Catania, Catania, I-95123, Italy)

  • VITO LATORA

    (Dipartimento di Fisica e Astronomia and Infn sezione di Catania, Universitá di Catania, Catania, I-95123, Italy)

  • ANDREA RAPISARDA

    (Dipartimento di Fisica e Astronomia and Infn sezione di Catania, Universitá di Catania, Catania, I-95123, Italy)

Abstract

We propose a new model of opinion formation, theOpinion Changing Rate(OCR) model. Instead of investigating the conditions that allow consensus in a world of agents with different opinions, we study the conditions under which a group of agents with different natural tendency (rate) to change opinion can find agreement. The OCR is a modified version of the Kuramoto model, one of the simplest models for synchronization in biological systems, adapted here to a social context. By means of several numerical simulations, we illustrate the richness of the OCR model dynamics and its social implications.

Suggested Citation

  • Alessandro Pluchino & Vito Latora & Andrea Rapisarda, 2005. "Changing Opinions In A Changing World: A New Perspective In Sociophysics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 515-531.
    • Handle: RePEc:wsi:ijmpcx:v:16:y:2005:i:04:n:s0129183105007261
    DOI: 10.1142/S0129183105007261
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    Citations

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    Cited by:

    1. Yao-feng Zhang & Hong-ye Duan & Zhi-lin Geng, 2017. "Evolutionary Mechanism of Frangibility in Social Consensus System Based on Negative Emotions Spread," Complexity, Hindawi, vol. 2017, pages 1-8, June.
    2. Biondo, A.E. & Pluchino, A. & Rapisarda, A., 2018. "Modeling surveys effects in political competitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 714-726.
    3. Xiao, Feng & Xie, Lingyun & Wei, Bo, 2022. "Explosive synchronization of weighted mobile oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    4. Young-Pil Choi, 2023. "On the rigorous derivation of hydrodynamics of the Kuramoto model for synchronization phenomena," Partial Differential Equations and Applications, Springer, vol. 4(1), pages 1-20, February.
    5. Tlaie, A. & Ballesteros-Esteban, L.M. & Leyva, I. & Sendiña-Nadal, I., 2019. "Statistical complexity and connectivity relationship in cultured neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 284-290.
    6. Le Pira, Michela & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea, 2017. "Finding shared decisions in stakeholder networks: An agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 277-287.
    7. Pawel Sobkowicz, 2009. "Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-11.
    8. Yaofeng Zhang & Renbin Xiao, 2015. "Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-15, August.
    9. Huang, Changwei & Luo, Yijun & Han, Wenchen, 2023. "Cooperation and synchronization in evolutionary opinion changing rate games," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    10. 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.
    11. Lacerda, Juliana C. & Freitas, Celso & Macau, Elbert E.N., 2022. "Elementary changes in topology and power transmission capacity can induce failures in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).

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