Long-term Behavior of Mean-field Noisy Bounded Confidence Models with Distributed Radicals

In this paper, we consider the mean-field model of noisy bounded confidence opinion dynamics under exogenous influence of static radical opinions. The long-term behavior of the model is analyzed by providing a sufficient condition for exponential convergence of the dynamics to stationary state. The...

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Bibliographic Details
Main Authors: Kolarijani, M. A. S., Proskurnikov, A. V., Esfahani, P. Mohajerin
Format: Conference Proceeding
Language:English
Online Access:Request full text
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Summary:In this paper, we consider the mean-field model of noisy bounded confidence opinion dynamics under exogenous influence of static radical opinions. The long-term behavior of the model is analyzed by providing a sufficient condition for exponential convergence of the dynamics to stationary state. The stationary state is also characterized by a global estimate for a sufficiently large noise. Furthermore, we consider the order-disorder transition in the model in order to identify the effect of the (relative) mass of the radicals on the critical noise level at which this transition occurs. A numerical scheme for approximating the critical noise level is provided and validated through numerical simulations of the mean-field model and the corresponding agent-based model for a particular distribution of radical opinions.
ISSN:2576-2370
DOI:10.1109/CDC40024.2019.9030212