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Three-State Opinion Model on Complex Topologies

We investigate opinion diffusion on complex networks and the interplay between the existence of neutral opinion states and non-trivial network structures. For this purpose, we apply a three-state opinion model based on magnetic-like interactions to modular complex networks, both synthetic and real n...

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Detalles Bibliográficos
Autores principales: Ferri, Irene, Pérez-Vicente, Conrad, Palassini, Matteo, Díaz-Guilera, Albert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689946/
https://www.ncbi.nlm.nih.gov/pubmed/36359717
http://dx.doi.org/10.3390/e24111627
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author Ferri, Irene
Pérez-Vicente, Conrad
Palassini, Matteo
Díaz-Guilera, Albert
author_facet Ferri, Irene
Pérez-Vicente, Conrad
Palassini, Matteo
Díaz-Guilera, Albert
author_sort Ferri, Irene
collection PubMed
description We investigate opinion diffusion on complex networks and the interplay between the existence of neutral opinion states and non-trivial network structures. For this purpose, we apply a three-state opinion model based on magnetic-like interactions to modular complex networks, both synthetic and real networks extracted from Twitter. The model allows for tuning the contribution of neutral agents using a neutrality parameter. We also consider social agitation, encoded as a temperature, that accounts for random opinion changes that are beyond the agent neighborhood opinion state. Using this model, we study which topological features influence the formation of consensus, bipartidism, or fragmentation of opinions in three parties, and how the neutrality parameter and the temperature interplay with the network structure.
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spelling pubmed-96899462022-11-25 Three-State Opinion Model on Complex Topologies Ferri, Irene Pérez-Vicente, Conrad Palassini, Matteo Díaz-Guilera, Albert Entropy (Basel) Article We investigate opinion diffusion on complex networks and the interplay between the existence of neutral opinion states and non-trivial network structures. For this purpose, we apply a three-state opinion model based on magnetic-like interactions to modular complex networks, both synthetic and real networks extracted from Twitter. The model allows for tuning the contribution of neutral agents using a neutrality parameter. We also consider social agitation, encoded as a temperature, that accounts for random opinion changes that are beyond the agent neighborhood opinion state. Using this model, we study which topological features influence the formation of consensus, bipartidism, or fragmentation of opinions in three parties, and how the neutrality parameter and the temperature interplay with the network structure. MDPI 2022-11-10 /pmc/articles/PMC9689946/ /pubmed/36359717 http://dx.doi.org/10.3390/e24111627 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ferri, Irene
Pérez-Vicente, Conrad
Palassini, Matteo
Díaz-Guilera, Albert
Three-State Opinion Model on Complex Topologies
title Three-State Opinion Model on Complex Topologies
title_full Three-State Opinion Model on Complex Topologies
title_fullStr Three-State Opinion Model on Complex Topologies
title_full_unstemmed Three-State Opinion Model on Complex Topologies
title_short Three-State Opinion Model on Complex Topologies
title_sort three-state opinion model on complex topologies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689946/
https://www.ncbi.nlm.nih.gov/pubmed/36359717
http://dx.doi.org/10.3390/e24111627
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