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Threshold Cascade Dynamics in Coevolving Networks

We study the coevolutionary dynamics of network topology and social complex contagion using a threshold cascade model. Our coevolving threshold model incorporates two mechanisms: the threshold mechanism for the spreading of a minority state such as a new opinion, idea, or innovation and the network...

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Detalles Bibliográficos
Autores principales: Min, Byungjoon, San Miguel, Maxi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297227/
https://www.ncbi.nlm.nih.gov/pubmed/37372273
http://dx.doi.org/10.3390/e25060929
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author Min, Byungjoon
San Miguel, Maxi
author_facet Min, Byungjoon
San Miguel, Maxi
author_sort Min, Byungjoon
collection PubMed
description We study the coevolutionary dynamics of network topology and social complex contagion using a threshold cascade model. Our coevolving threshold model incorporates two mechanisms: the threshold mechanism for the spreading of a minority state such as a new opinion, idea, or innovation and the network plasticity, implemented as the rewiring of links to cut the connections between nodes in different states. Using numerical simulations and a mean-field theoretical analysis, we demonstrate that the coevolutionary dynamics can significantly affect the cascade dynamics. The domain of parameters, i.e., the threshold and mean degree, for which global cascades occur shrinks with an increasing network plasticity, indicating that the rewiring process suppresses the onset of global cascades. We also found that during evolution, non-adopting nodes form denser connections, resulting in a wider degree distribution and a non-monotonous dependence of cascades sizes on plasticity.
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spelling pubmed-102972272023-06-28 Threshold Cascade Dynamics in Coevolving Networks Min, Byungjoon San Miguel, Maxi Entropy (Basel) Article We study the coevolutionary dynamics of network topology and social complex contagion using a threshold cascade model. Our coevolving threshold model incorporates two mechanisms: the threshold mechanism for the spreading of a minority state such as a new opinion, idea, or innovation and the network plasticity, implemented as the rewiring of links to cut the connections between nodes in different states. Using numerical simulations and a mean-field theoretical analysis, we demonstrate that the coevolutionary dynamics can significantly affect the cascade dynamics. The domain of parameters, i.e., the threshold and mean degree, for which global cascades occur shrinks with an increasing network plasticity, indicating that the rewiring process suppresses the onset of global cascades. We also found that during evolution, non-adopting nodes form denser connections, resulting in a wider degree distribution and a non-monotonous dependence of cascades sizes on plasticity. MDPI 2023-06-13 /pmc/articles/PMC10297227/ /pubmed/37372273 http://dx.doi.org/10.3390/e25060929 Text en © 2023 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
Min, Byungjoon
San Miguel, Maxi
Threshold Cascade Dynamics in Coevolving Networks
title Threshold Cascade Dynamics in Coevolving Networks
title_full Threshold Cascade Dynamics in Coevolving Networks
title_fullStr Threshold Cascade Dynamics in Coevolving Networks
title_full_unstemmed Threshold Cascade Dynamics in Coevolving Networks
title_short Threshold Cascade Dynamics in Coevolving Networks
title_sort threshold cascade dynamics in coevolving networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297227/
https://www.ncbi.nlm.nih.gov/pubmed/37372273
http://dx.doi.org/10.3390/e25060929
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