Breaking Consensus in Kinetic Opinion Formation Models on Graphons

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Main Authors: Düring, Bertram, Franceschi, Jonathan, Wolfram, Marie-Therese, Zanella, Mattia
Format: Preprint
Published: 2024
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author Düring, Bertram
Franceschi, Jonathan
Wolfram, Marie-Therese
Zanella, Mattia
author_facet Düring, Bertram
Franceschi, Jonathan
Wolfram, Marie-Therese
Zanella, Mattia
contents In this work we propose and investigate a strategy to prevent consensus in kinetic models for opinion formation. We consider a large interacting agent system, and assume that agent interactions are driven by compromise as well as self-thinking dynamics and also modulated by an underlying static social network. This network structure is included using so-called graphons, which modulate the interaction frequency in the corresponding kinetic formulation. We then derive the corresponding limiting Fokker Planck equation, and analyze its large time behavior. This microscopic setting serves as a starting point for the proposed control strategy, which steers agents away from mean opinion and is characterised by a suitable penalization depending on the properties of the graphon. We show that this minimalist approach is very effective by analyzing the quasi-stationary solutions mean-field model in a plurality of graphon structures. Several numerical experiments are also provided to show the effectiveness of the approach in preventing the formation of consensus steering the system towards a declustered state.
format Preprint
id arxiv_https___arxiv_org_abs_2403_14431
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Breaking Consensus in Kinetic Opinion Formation Models on Graphons
Düring, Bertram
Franceschi, Jonathan
Wolfram, Marie-Therese
Zanella, Mattia
Mathematical Physics
Analysis of PDEs
Optimization and Control
Physics and Society
In this work we propose and investigate a strategy to prevent consensus in kinetic models for opinion formation. We consider a large interacting agent system, and assume that agent interactions are driven by compromise as well as self-thinking dynamics and also modulated by an underlying static social network. This network structure is included using so-called graphons, which modulate the interaction frequency in the corresponding kinetic formulation. We then derive the corresponding limiting Fokker Planck equation, and analyze its large time behavior. This microscopic setting serves as a starting point for the proposed control strategy, which steers agents away from mean opinion and is characterised by a suitable penalization depending on the properties of the graphon. We show that this minimalist approach is very effective by analyzing the quasi-stationary solutions mean-field model in a plurality of graphon structures. Several numerical experiments are also provided to show the effectiveness of the approach in preventing the formation of consensus steering the system towards a declustered state.
title Breaking Consensus in Kinetic Opinion Formation Models on Graphons
topic Mathematical Physics
Analysis of PDEs
Optimization and Control
Physics and Society
url https://arxiv.org/abs/2403.14431