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

Conference Paper (2019)
Author(s)

M. A.S. Kolarijani (TU Delft - Team Peyman Mohajerin Esfahani)

A. V. Proskurnikov (Russian Academy of Sciences, Politecnico di Torino)

P. Mohajerin Esfahani (TU Delft - Team Peyman Mohajerin Esfahani, TU Delft - Team Bart De Schutter)

DOI related publication
https://doi.org/10.1109/CDC40024.2019.9030212 Final published version
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Publication Year
2019
Language
English
Pages (from-to)
6158-6163
ISBN (electronic)
978-1-7281-1398-2
Event
58th IEEE Conference on Decision and Control, CDC 2019 (2019-12-11 - 2019-12-13), Nice, France
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Abstract

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.

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