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The Evolution of Political Views Within the Model with Two Binary Opinions

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Computational Science – ICCS 2021 (ICCS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12744))

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Abstract

We study a model aimed to describe political views within two-dimensional approach, known as the Nolan chart or the political compass, which distinguish between opinions related to economic and personal freedom. We conduct Monte Carlo simulations and show that in the lack of noise, i.e. at social temperature \(T=0\), the consensus is impossible if there is a coupling between opinions related to economic and personal freedom. Moreover, for \(T>0\) we show how the strength of the coupling between these opinions can hamper or facilitate the consensus.

Supported by the National Science Center (NCN, Poland) through Grant No. 2016/21/B/HS6/01256.

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Authors and Affiliations

  1. Department of Theoretical Physics, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Magdalena Gołȩbiowska & Katarzyna Sznajd-Weron

Authors
  1. Magdalena Gołȩbiowska
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  2. Katarzyna Sznajd-Weron
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Corresponding author

Correspondence to Katarzyna Sznajd-Weron .

Editor information

Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Dieter Kranzlmüller

  3. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  4. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  5. University of Amsterdam, Amsterdam, The Netherlands

    Peter M.A. Sloot

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Gołȩbiowska, M., Sznajd-Weron, K. (2021). The Evolution of Political Views Within the Model with Two Binary Opinions. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12744. Springer, Cham. https://doi.org/10.1007/978-3-030-77967-2_25

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  • DOI: https://doi.org/10.1007/978-3-030-77967-2_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77966-5

  • Online ISBN: 978-3-030-77967-2

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