Abstract
Empirical evidences have supported the large heterogeneity in the timing of individuals' activities. Moreover, computational analysis of the agent-based models has shown the importance of the activation regimes. 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 also the number of emergent extremists. The results exhibit both qualitative and quantitative difference between different activation regimes which in some cases are counterintuitive. In particular, we find that exposing the radical/moderate agents to more encounters decreases/increases the average number of extremists compared to other types of activation regimes. The results also show that no specific updating scheme can always outperform the others in reaching to consensus.
Highlights
1.1 The term "opinion dynamics" refers to a wide range of models in the social psychology, sociology, physics, and computer science literatures
First we show the general behavior of the opinion dynamics model according to four different activation regimes
We use the emergent opinion clusters' statistics and the number of extremists to compare the output of opinion dynamics model according to different activation regimes
Summary
1.1 The term "opinion dynamics" refers to a wide range of models in the social psychology, sociology, physics, and computer science literatures. These models differ in terms of the phenomena of interest, the underlying assumptions and theories, the activation regimes, and updating rules. First are models that are based on statistical physics (Weidlich 1971; Sznajd-Weron 2000; Galam 2005). The underlying concept of these models is a "transition rate" between different states of a social system, and opinion dynamics is considered in terms of order-disorder transitions (Kurmyshev et al 2011). The second category of models is agent-based models. The emerging behavior of the social system is studied through the interactions of independent and autonomous agents.
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