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Analytical results for the Sznajd model of opinion formation

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  • F. Slanina
  • H. Lavicka

Abstract

The Sznajd model, which describes opinion formation and social influence, is treated analytically on a complete graph. We prove the existence of the phase transition in the original formulation of the model, while for the Ochrombel modification we find smooth behaviour without transition. We calculate the average time to reach the stationary state as well as the exponential tail of its probability distribution. An analytical argument for the observed 1/n dependence in the distribution of votes in Brazilian elections is provided. Copyright Springer-Verlag Berlin/Heidelberg 2003

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  • F. Slanina & H. Lavicka, 2003. "Analytical results for the Sznajd model of opinion formation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 35(2), pages 279-288, September.
    • Handle: RePEc:spr:eurphb:v:35:y:2003:i:2:p:279-288
    DOI: 10.1140/epjb/e2003-00278-0
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    Cited by:

    1. Erik Cuevas & Alberto Luque & Fernando Vega & Daniel Zaldívar & Jesús López, 2024. "Social influence dynamics for image segmentation: a novel pixel interaction approach," Journal of Computational Social Science, Springer, vol. 7(3), pages 2613-2642, December.
    2. Düring, B. & Toscani, G., 2007. "Hydrodynamics from kinetic models of conservative economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 493-506.
    3. Czaplicka, Agnieszka & Charalambous, Christos & Toral, Raul & San Miguel, Maxi, 2022. "Biased-voter model: How persuasive a small group can be?," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    4. Grabowski, Andrzej, 2009. "Opinion formation in a social network: The role of human activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 961-966.
    5. 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).
    6. Sznajd-Weron, Katarzyna & Sznajd, Józef & Weron, Tomasz, 2021. "A review on the Sznajd model — 20 years after," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    7. Fang, Siwei & Zhao, Nan & Chen, Nan & Xiong, Fei & Yi, Yunhui, 2019. "Analyzing and predicting network public opinion evolution based on group persuasion force of populism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 809-824.
    8. Bertram During & Nicos Georgiou & Enrico Scalas, 2016. "A stylized model for wealth distribution," Papers 1609.08978, arXiv.org, revised Jul 2021.
    9. 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.
    10. Lücke, Marvin & Heitzig, Jobst & Koltai, Péter & Molkenthin, Nora & Winkelmann, Stefanie, 2023. "Large population limits of Markov processes on random networks," Stochastic Processes and their Applications, Elsevier, vol. 166(C).
    11. Pérez-Llanos, Mayte & Pinasco, Juan Pablo & Saintier, Nicolas, 2020. "Opinion attractiveness and its effect in opinion formation models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    12. Sven Banischa & Ricardo Lima & Tanya Araújo, 2012. "Agent based models and opinion dynamics as markov chains," Working Papers Department of Economics 2012/10, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    13. Galam, Serge, 2010. "Public debates driven by incomplete scientific data: The cases of evolution theory, global warming and H1N1 pandemic influenza," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3619-3631.
    14. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    15. Jin, Cheng & Li, Yifu & Jin, Xiaogang, 2017. "Political opinion formation: Initial opinion distribution and individual heterogeneity of tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 257-266.
    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. Zhong, Yue & Lai, Shaoyong & Hu, Chunhua, 2021. "Investigations to the dynamics of wealth distribution in a kinetic exchange model," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    18. Grabowski, A. & Kosiński, R.A., 2006. "Ising-based model of opinion formation in a complex network of interpersonal interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(2), pages 651-664.

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