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The role of persuasion power on the consensus formation

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  • Gündüç, Semra
  • Eryiğit, Recep

Abstract

An opinion dynamics model which is based on a version of two dimensional Sznajd model is introduced. According to this model the dynamics is governed by the interactions between four agents which live on the corners of a plaquette and their neighbors. The distinctive feature of the model is that each individual is identified by two parameters, namely, opinion and persuasion ability. The united group may persuade the individuals living at the neighboring sites according to both the number and their persuasion ability. This form of the model is used to discuss opinion dynamics processes in societies where a campaign is conducted by the principle being united and putting forward arguments which are commonly accepted by the members of the society. It is seen that persuasion parameter plays the major role in the societies where a minority opinion gains ground to be the major opinion of the society. The model has been applied to the Scottish referendum opinion poles data since 2011. The model in its simplicity, predicts that the arguments of the minority opinion (“YES” votes) are more appealing despite the observed win of the “NO” votes. This result may be due to the abundance of the “NO” opinion supporters at the beginning of the campaign.

Suggested Citation

  • Gündüç, Semra & Eryiğit, Recep, 2015. "The role of persuasion power on the consensus formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 16-24.
    • Handle: RePEc:eee:phsmap:v:426:y:2015:i:c:p:16-24
    DOI: 10.1016/j.physa.2015.01.040
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    References listed on IDEAS

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    1. Sznajd-Weron, K. & Weron, R., 2003. "How effective is advertising in duopoly markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 437-444.
    2. 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.
    3. Lorenzo Sabatelli & Peter Richmond, 2003. "Phase Transitions, Memory And Frustration In A Sznajd-Like Model With Synchronous Updating," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(09), pages 1223-1229.
    4. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    5. B. M. Roehner & D. Sornette & J. V. Andersen, 2004. "Response Functions To Critical Shocks In Social Sciences: An Empirical And Numerical Study," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 809-834.
    6. Sabatelli, Lorenzo & Richmond, Peter, 2004. "Non-monotonic spontaneous magnetization in a Sznajd-like consensus model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 274-280.
    7. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    8. Christian Schulze, 2003. "Advertising In The Sznajd Marketing Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 95-98.
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