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Interplay between collective behavior and spreading dynamics on complex networks

There are certain correlations between collective behavior and spreading dynamics on some real complex networks. Based on the dynamical characteristics and traditional physical models, we construct several new bidirectional network models of spreading phenomena. By theoretical and numerical analysis...

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Detalles Bibliográficos
Autores principales: Li, Kezan, Ma, Zhongjun, Jia, Zhen, Small, Michael, Fu, Xinchu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Institute of Physics 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112518/
https://www.ncbi.nlm.nih.gov/pubmed/23278048
http://dx.doi.org/10.1063/1.4766677
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author Li, Kezan
Ma, Zhongjun
Jia, Zhen
Small, Michael
Fu, Xinchu
author_facet Li, Kezan
Ma, Zhongjun
Jia, Zhen
Small, Michael
Fu, Xinchu
author_sort Li, Kezan
collection PubMed
description There are certain correlations between collective behavior and spreading dynamics on some real complex networks. Based on the dynamical characteristics and traditional physical models, we construct several new bidirectional network models of spreading phenomena. By theoretical and numerical analysis of these models, we find that the collective behavior can inhibit spreading behavior, but, conversely, this spreading behavior can accelerate collective behavior. The spread threshold of spreading network is obtained by using the Lyapunov function method. The results show that an effective spreading control method is to enhance the individual awareness to collective behavior. Many real-world complex networks can be thought of in terms of both collective behavior and spreading dynamics and therefore to better understand and control such complex networks systems, our work may provide a basic framework.
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spelling pubmed-71125182020-04-02 Interplay between collective behavior and spreading dynamics on complex networks Li, Kezan Ma, Zhongjun Jia, Zhen Small, Michael Fu, Xinchu Chaos Regular Articles There are certain correlations between collective behavior and spreading dynamics on some real complex networks. Based on the dynamical characteristics and traditional physical models, we construct several new bidirectional network models of spreading phenomena. By theoretical and numerical analysis of these models, we find that the collective behavior can inhibit spreading behavior, but, conversely, this spreading behavior can accelerate collective behavior. The spread threshold of spreading network is obtained by using the Lyapunov function method. The results show that an effective spreading control method is to enhance the individual awareness to collective behavior. Many real-world complex networks can be thought of in terms of both collective behavior and spreading dynamics and therefore to better understand and control such complex networks systems, our work may provide a basic framework. American Institute of Physics 2012-12 2012-11-26 /pmc/articles/PMC7112518/ /pubmed/23278048 http://dx.doi.org/10.1063/1.4766677 Text en Copyright © 2012 American Institute of Physics 1054-1500/2012/22(4)/043113/10/$30.00 All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).
spellingShingle Regular Articles
Li, Kezan
Ma, Zhongjun
Jia, Zhen
Small, Michael
Fu, Xinchu
Interplay between collective behavior and spreading dynamics on complex networks
title Interplay between collective behavior and spreading dynamics on complex networks
title_full Interplay between collective behavior and spreading dynamics on complex networks
title_fullStr Interplay between collective behavior and spreading dynamics on complex networks
title_full_unstemmed Interplay between collective behavior and spreading dynamics on complex networks
title_short Interplay between collective behavior and spreading dynamics on complex networks
title_sort interplay between collective behavior and spreading dynamics on complex networks
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112518/
https://www.ncbi.nlm.nih.gov/pubmed/23278048
http://dx.doi.org/10.1063/1.4766677
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