How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs

Real-world networks are typically characterised by a non-trivial organization at the mesoscale, such that groups of nodes are preferentially connected within distinguishable network regions known as communities. In this work the authors define unipartite, bipartite, and multilayer network representa...

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Detalles Bibliográficos
Autores principales:	Anton Eriksson, Daniel Edler, Alexis Rojas, Manlio de Domenico, Martin Rosvall
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Astrophysics QB460-466 Physics QC1-999
Acceso en línea:	https://doaj.org/article/37ecc9c24c0241d3a054f8f4fca408db
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spelling	oai:doaj.org-article:37ecc9c24c0241d3a054f8f4fca408db2021-12-02T14:59:28ZHow choosing random-walk model and network representation matters for flow-based community detection in hypergraphs10.1038/s42005-021-00634-z2399-3650https://doaj.org/article/37ecc9c24c0241d3a054f8f4fca408db2021-06-01T00:00:00Zhttps://doi.org/10.1038/s42005-021-00634-zhttps://doaj.org/toc/2399-3650Real-world networks are typically characterised by a non-trivial organization at the mesoscale, such that groups of nodes are preferentially connected within distinguishable network regions known as communities. In this work the authors define unipartite, bipartite, and multilayer network representations of hypergraph flows to extract the community structure of social and biological systems with higher-order interactions.Anton ErikssonDaniel EdlerAlexis RojasManlio de DomenicoMartin RosvallNature PortfolioarticleAstrophysicsQB460-466PhysicsQC1-999ENCommunications Physics, Vol 4, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Astrophysics QB460-466 Physics QC1-999
spellingShingle	Astrophysics QB460-466 Physics QC1-999 Anton Eriksson Daniel Edler Alexis Rojas Manlio de Domenico Martin Rosvall How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
description	Real-world networks are typically characterised by a non-trivial organization at the mesoscale, such that groups of nodes are preferentially connected within distinguishable network regions known as communities. In this work the authors define unipartite, bipartite, and multilayer network representations of hypergraph flows to extract the community structure of social and biological systems with higher-order interactions.
format	article
author	Anton Eriksson Daniel Edler Alexis Rojas Manlio de Domenico Martin Rosvall
author_facet	Anton Eriksson Daniel Edler Alexis Rojas Manlio de Domenico Martin Rosvall
author_sort	Anton Eriksson
title	How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
title_short	How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
title_full	How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
title_fullStr	How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
title_full_unstemmed	How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
title_sort	how choosing random-walk model and network representation matters for flow-based community detection in hypergraphs
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/37ecc9c24c0241d3a054f8f4fca408db
work_keys_str_mv	AT antoneriksson howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs AT danieledler howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs AT alexisrojas howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs AT manliodedomenico howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs AT martinrosvall howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs
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How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs

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