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Few Self-Involved Agents Among Bounded Confidence Agents Can Change Norms

Author

Listed:
  • SYLVIE HUET

    (Irstea, Laboratory of Engineering for Complex Systems LISC, 63172 Aubière, France)

  • JEAN-DENIS MATHIAS

    (Irstea, Laboratory of Engineering for Complex Systems LISC, 63172 Aubière, France)

Abstract

Social issues are generally discussed by highly-involved and less-involved people to build social norms defining what has to be thought and done about them. As self-involved agents share different attitude dynamics to other agents [Wood, W., Pool, G., Leck, K. and Purvis, D., Self-definition, defensive processing, and influence: The normative impact of majority and minority groups, J. Pers. Soc. Psychol. (1996) 1181–1193], we study the emergence and evolution of norms through an individual-based model involving these two types of agents. The dynamics of self-involved agents is drawn from [Huet, S. and Deffuant, G., Openness leads to opinion stability and narrowness to volatility, Adv. Complex Syst. 13 (2010) 405–423], and the dynamics of others, from [Deffuant, G., Neau, D., Amblard, F. and Weisbuch, G., Mixing beliefs among interacting agents, Adv. Complex Syst. 3 (2001) 87–98]. The attitude of an agent is represented as a segment on a continuous attitudinal space. Two agents are close if their attitude segments share sufficient overlap. Our agents discuss two different issues, one of which, called main issue, is more important for the self-involved agents than the other, called secondary issue. Self-involved agents are attracted to both issues if they are close to the main issue, but shift away from their peer’s opinion if they are only close on the secondary issue. Differently, non-self-involved agents are attracted by other agents when they are close on both the main and secondary issues. We observe the emergence of various types of extreme minor clusters. In one or different groups of attitudes, they can lead to an already-built moderate norm or a norm polarized on secondary and/or main issues. They can also push disagreeing agents gathered in different groups to a global moderate consensus.

Suggested Citation

  • Sylvie Huet & Jean-Denis Mathias, 2018. "Few Self-Involved Agents Among Bounded Confidence Agents Can Change Norms," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-27, September.
    • Handle: RePEc:wsi:acsxxx:v:21:y:2018:i:06n07:n:s0219525918500078
    DOI: 10.1142/S0219525918500078
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    References listed on IDEAS

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    1. Jan Lorenz, 2007. "Continuous Opinion Dynamics Under Bounded Confidence: A Survey," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(12), pages 1819-1838.
    2. 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.
    3. Guillaume Deffuant & Frederic Amblard & Gérard Weisbuch, 2002. "How Can Extremism Prevail? a Study Based on the Relative Agreement Interaction Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1-1.
    4. Farrow, Katherine & Grolleau, Gilles & Ibanez, Lisette, 2017. "Social Norms and Pro-environmental Behavior: A Review of the Evidence," Ecological Economics, Elsevier, vol. 140(C), pages 1-13.
    5. Sylvie Huet & Guillaume Deffuant, 2010. "Openness Leads To Opinion Stability And Narrowness To Volatility," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 405-423.
    6. Mathias, Jean-Denis & Huet, Sylvie & Deffuant, Guillaume, 2017. "An energy-like indicator to assess opinion resilience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 501-510.
    7. Laurent Salzarulo, 2006. "A Continuous Opinion Dynamics Model Based on the Principle of Meta-Contrast," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-13.
    8. Jean-Denis Mathias & Sylvie Huet & Guillaume Deffuant, 2016. "Bounded Confidence Model with Fixed Uncertainties and Extremists: The Opinions Can Keep Fluctuating Indefinitely," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-6.
    9. Andreas Flache & Michael Mäs & Thomas Feliciani & Edmund Chattoe-Brown & Guillaume Deffuant & Sylvie Huet & Jan Lorenz, 2017. "Models of Social Influence: Towards the Next Frontiers," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(4), pages 1-2.
    10. Guillaume Deffuant, 2006. "Comparing Extremism Propagation Patterns in Continuous Opinion Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(3), pages 1-8.
    11. repec:sae:jocore:v:55:y:2011:i:6:p:970-955 is not listed on IDEAS
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