Characterizing the interactions between classical and community-aware centrality measures in complex networks

Abstract Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recent works have shown that community-aware centrality measures compare favorably with classical measures agnostic...

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Autores principales:	Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/201556cd3d914967a4ca3b6c902e4741
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id	oai:doaj.org-article:201556cd3d914967a4ca3b6c902e4741
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spelling	oai:doaj.org-article:201556cd3d914967a4ca3b6c902e47412021-12-02T17:15:59ZCharacterizing the interactions between classical and community-aware centrality measures in complex networks10.1038/s41598-021-89549-x2045-2322https://doaj.org/article/201556cd3d914967a4ca3b6c902e47412021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89549-xhttps://doaj.org/toc/2045-2322Abstract Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recent works have shown that community-aware centrality measures compare favorably with classical measures agnostic about this ubiquitous property. Nonetheless, there is no clear consensus about how they relate and in which situation it is better to use a classical or a community-aware centrality measure. To this end, in this paper, we perform an extensive investigation to get a better understanding of the relationship between classical and community-aware centrality measures reported in the literature. Experiments use artificial networks with controlled community structure properties and a large sample of real-world networks originating from various domains. Results indicate that the stronger the community structure, the more appropriate the community-aware centrality measures. Furthermore, variations of the degree and community size distribution parameters do not affect the results. Finally, network transitivity and community structure strength are the most significant drivers controlling the interactions between classical and community-aware centrality measures.Stephany RajehMarinette SavonnetEric LeclercqHocine CherifiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Stephany Rajeh Marinette Savonnet Eric Leclercq Hocine Cherifi Characterizing the interactions between classical and community-aware centrality measures in complex networks
description	Abstract Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recent works have shown that community-aware centrality measures compare favorably with classical measures agnostic about this ubiquitous property. Nonetheless, there is no clear consensus about how they relate and in which situation it is better to use a classical or a community-aware centrality measure. To this end, in this paper, we perform an extensive investigation to get a better understanding of the relationship between classical and community-aware centrality measures reported in the literature. Experiments use artificial networks with controlled community structure properties and a large sample of real-world networks originating from various domains. Results indicate that the stronger the community structure, the more appropriate the community-aware centrality measures. Furthermore, variations of the degree and community size distribution parameters do not affect the results. Finally, network transitivity and community structure strength are the most significant drivers controlling the interactions between classical and community-aware centrality measures.
format	article
author	Stephany Rajeh Marinette Savonnet Eric Leclercq Hocine Cherifi
author_facet	Stephany Rajeh Marinette Savonnet Eric Leclercq Hocine Cherifi
author_sort	Stephany Rajeh
title	Characterizing the interactions between classical and community-aware centrality measures in complex networks
title_short	Characterizing the interactions between classical and community-aware centrality measures in complex networks
title_full	Characterizing the interactions between classical and community-aware centrality measures in complex networks
title_fullStr	Characterizing the interactions between classical and community-aware centrality measures in complex networks
title_full_unstemmed	Characterizing the interactions between classical and community-aware centrality measures in complex networks
title_sort	characterizing the interactions between classical and community-aware centrality measures in complex networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/201556cd3d914967a4ca3b6c902e4741
work_keys_str_mv	AT stephanyrajeh characterizingtheinteractionsbetweenclassicalandcommunityawarecentralitymeasuresincomplexnetworks AT marinettesavonnet characterizingtheinteractionsbetweenclassicalandcommunityawarecentralitymeasuresincomplexnetworks AT ericleclercq characterizingtheinteractionsbetweenclassicalandcommunityawarecentralitymeasuresincomplexnetworks AT hocinecherifi characterizingtheinteractionsbetweenclassicalandcommunityawarecentralitymeasuresincomplexnetworks
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Characterizing the interactions between classical and community-aware centrality measures in complex networks

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