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Activation Regimes in Opinion Dynamics: Comparing Asynchronous Updating Schemes

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Abstract

Empirical evidence shows significant heterogeneity in the timing of individuals' activities. Moreover, computational analysis of agent-based models has shown the importance of the activation regime. In this paper, we apply four different asynchronous updating schemes, including random, uniform, and two state-driven Poisson updating schemes on an agent-based opinion dynamics model. We compare the effect of these activation regimes by measuring the appropriate opinion clustering statistics and the number of emergent extremists. Results exhibit both qualitative and quantitative difference among activation regimes, including some counterintuitive cases. In particular, we find that exposing radical/moderate agents to more encounters decreases/increases the average number of extremists compared to other types of activation regimes. Results also show that no specific updating scheme can always outperform the others in reaching consensus.

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  • Meysam Alizadeh & Claudio Cioffi-Revilla, 2015. "Activation Regimes in Opinion Dynamics: Comparing Asynchronous Updating Schemes," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-8.
    • Handle: RePEc:jas:jasssj:2014-56-3
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    Cited by:

    1. Zhaogang Ding & Yucheng Dong & Haiming Liang & Francisco Chiclana, 2017. "Asynchronous Opinion Dynamics with Online and Offline Interactions in Bounded Confidence Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(4), pages 1-6.
    2. Meysam Alizadeh & Claudio Cioffi-Revilla & Andrew Crooks, 2015. "The Effect Of In-Group Favoritism On The Collective Behavior Of Individuals' Opinions," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 18(01n02), pages 1-26.
    3. Mehrdad Agha Mohammad Ali Kermani & Reza Ghesmati & Masoud Jalayer, 2018. "Opinion-Aware Influence Maximization: How To Maximize A Favorite Opinion In A Social Network?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-27, September.
    4. 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.
    5. Serge Galam & Marco Alberto Javarone, 2016. "Modeling Radicalization Phenomena in Heterogeneous Populations," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-15, May.

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