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Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure

We present a study of the dynamic interactions between actors located on complex networks with scale-free and hierarchical scale-free topologies with assortative mixing, that is, correlations between the degree distributions of the actors. The actor’s state evolves according to a model that consider...

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Autores principales: Jacobo-Villegas, Eduardo, Obregón-Quintana, Bibiana, Guzmán-Vargas, Lev, Liebovitch, Larry S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689849/
https://www.ncbi.nlm.nih.gov/pubmed/36359665
http://dx.doi.org/10.3390/e24111571
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author Jacobo-Villegas, Eduardo
Obregón-Quintana, Bibiana
Guzmán-Vargas, Lev
Liebovitch, Larry S.
author_facet Jacobo-Villegas, Eduardo
Obregón-Quintana, Bibiana
Guzmán-Vargas, Lev
Liebovitch, Larry S.
author_sort Jacobo-Villegas, Eduardo
collection PubMed
description We present a study of the dynamic interactions between actors located on complex networks with scale-free and hierarchical scale-free topologies with assortative mixing, that is, correlations between the degree distributions of the actors. The actor’s state evolves according to a model that considers its previous state, the inertia to change, and the influence of its neighborhood. We show that the time evolution of the system depends on the percentage of cooperative or competitive interactions. For scale-free networks, we find that the dispersion between actors is higher when all interactions are either cooperative or competitive, while a balanced presence of interactions leads to a lower separation. Moreover, positive assortative mixing leads to greater divergence between the states, while negative assortative mixing reduces this dispersion. We also find that hierarchical scale-free networks have both similarities and differences when compared with scale-free networks. Hierarchical scale-free networks, like scale-free networks, show the least divergence for an equal mix of cooperative and competitive interactions between actors. On the other hand, hierarchical scale-free networks, unlike scale-free networks, show much greater divergence when dominated by cooperative rather than competitive actors, and while the formation of a rich club (adding links between hubs) with cooperative interactions leads to greater divergence, the divergence is much less when they are fully competitive. Our findings highlight the importance of the topology where the interaction dynamics take place, and the fact that a balanced presence of cooperators and competitors makes the system more cohesive, compared to the case where one strategy dominates.
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spelling pubmed-96898492022-11-25 Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure Jacobo-Villegas, Eduardo Obregón-Quintana, Bibiana Guzmán-Vargas, Lev Liebovitch, Larry S. Entropy (Basel) Article We present a study of the dynamic interactions between actors located on complex networks with scale-free and hierarchical scale-free topologies with assortative mixing, that is, correlations between the degree distributions of the actors. The actor’s state evolves according to a model that considers its previous state, the inertia to change, and the influence of its neighborhood. We show that the time evolution of the system depends on the percentage of cooperative or competitive interactions. For scale-free networks, we find that the dispersion between actors is higher when all interactions are either cooperative or competitive, while a balanced presence of interactions leads to a lower separation. Moreover, positive assortative mixing leads to greater divergence between the states, while negative assortative mixing reduces this dispersion. We also find that hierarchical scale-free networks have both similarities and differences when compared with scale-free networks. Hierarchical scale-free networks, like scale-free networks, show the least divergence for an equal mix of cooperative and competitive interactions between actors. On the other hand, hierarchical scale-free networks, unlike scale-free networks, show much greater divergence when dominated by cooperative rather than competitive actors, and while the formation of a rich club (adding links between hubs) with cooperative interactions leads to greater divergence, the divergence is much less when they are fully competitive. Our findings highlight the importance of the topology where the interaction dynamics take place, and the fact that a balanced presence of cooperators and competitors makes the system more cohesive, compared to the case where one strategy dominates. MDPI 2022-10-31 /pmc/articles/PMC9689849/ /pubmed/36359665 http://dx.doi.org/10.3390/e24111571 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
Jacobo-Villegas, Eduardo
Obregón-Quintana, Bibiana
Guzmán-Vargas, Lev
Liebovitch, Larry S.
Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
title Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
title_full Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
title_fullStr Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
title_full_unstemmed Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
title_short Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
title_sort conflict dynamics in scale-free networks with degree correlations and hierarchical structure
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689849/
https://www.ncbi.nlm.nih.gov/pubmed/36359665
http://dx.doi.org/10.3390/e24111571
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