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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Main Authors: Anton Eriksson, Daniel Edler, Alexis Rojas, Manlio de Domenico, Martin Rosvall
Format: article
Language:EN
Published: Nature Portfolio 2021
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Online Access: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
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AT danieledler howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs
AT alexisrojas howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs
AT manliodedomenico howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs
AT martinrosvall howchoosingrandomwalkmodelandnetworkrepresentationmattersforflowbasedcommunitydetectioninhypergraphs
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