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Profiling core-periphery network structure by random walkers

Disclosing the main features of the structure of a network is crucial to understand a number of static and dynamic properties, such as robustness to failures, spreading dynamics, or collective behaviours. Among the possible characterizations, the core-periphery paradigm models the network as the uni...

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Detalles Bibliográficos
Autores principales: Rossa, Fabio Della, Dercole, Fabio, Piccardi, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3601366/
https://www.ncbi.nlm.nih.gov/pubmed/23507984
http://dx.doi.org/10.1038/srep01467
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author Rossa, Fabio Della
Dercole, Fabio
Piccardi, Carlo
author_facet Rossa, Fabio Della
Dercole, Fabio
Piccardi, Carlo
author_sort Rossa, Fabio Della
collection PubMed
description Disclosing the main features of the structure of a network is crucial to understand a number of static and dynamic properties, such as robustness to failures, spreading dynamics, or collective behaviours. Among the possible characterizations, the core-periphery paradigm models the network as the union of a dense core with a sparsely connected periphery, highlighting the role of each node on the basis of its topological position. Here we show that the core-periphery structure can effectively be profiled by elaborating the behaviour of a random walker. A curve—the core-periphery profile—and a numerical indicator are derived, providing a global topological portrait. Simultaneously, a coreness value is attributed to each node, qualifying its position and role. The application to social, technological, economical, and biological networks reveals the power of this technique in disclosing the overall network structure and the peculiar role of some specific nodes.
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spelling pubmed-36013662013-03-19 Profiling core-periphery network structure by random walkers Rossa, Fabio Della Dercole, Fabio Piccardi, Carlo Sci Rep Article Disclosing the main features of the structure of a network is crucial to understand a number of static and dynamic properties, such as robustness to failures, spreading dynamics, or collective behaviours. Among the possible characterizations, the core-periphery paradigm models the network as the union of a dense core with a sparsely connected periphery, highlighting the role of each node on the basis of its topological position. Here we show that the core-periphery structure can effectively be profiled by elaborating the behaviour of a random walker. A curve—the core-periphery profile—and a numerical indicator are derived, providing a global topological portrait. Simultaneously, a coreness value is attributed to each node, qualifying its position and role. The application to social, technological, economical, and biological networks reveals the power of this technique in disclosing the overall network structure and the peculiar role of some specific nodes. Nature Publishing Group 2013-03-19 /pmc/articles/PMC3601366/ /pubmed/23507984 http://dx.doi.org/10.1038/srep01467 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Article
Rossa, Fabio Della
Dercole, Fabio
Piccardi, Carlo
Profiling core-periphery network structure by random walkers
title Profiling core-periphery network structure by random walkers
title_full Profiling core-periphery network structure by random walkers
title_fullStr Profiling core-periphery network structure by random walkers
title_full_unstemmed Profiling core-periphery network structure by random walkers
title_short Profiling core-periphery network structure by random walkers
title_sort profiling core-periphery network structure by random walkers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3601366/
https://www.ncbi.nlm.nih.gov/pubmed/23507984
http://dx.doi.org/10.1038/srep01467
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