Revealing Consensus and Dissensus between Network Partitions

Community detection methods attempt to divide a network into groups of nodes that share similar properties, thus revealing its large-scale structure. A major challenge when employing such methods is that they are often degenerate, typically yielding a complex landscape of competing answers. As an at...

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Autor principal:	Tiago P. Peixoto
Formato:	article
Lenguaje:	EN
Publicado:	American Physical Society 2021
Materias:	Physics QC1-999
Acceso en línea:	https://doaj.org/article/79f3b4f4847d408eb286f3bdd273ccd4
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id	oai:doaj.org-article:79f3b4f4847d408eb286f3bdd273ccd4
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spelling	oai:doaj.org-article:79f3b4f4847d408eb286f3bdd273ccd42021-12-02T14:24:33ZRevealing Consensus and Dissensus between Network Partitions10.1103/PhysRevX.11.0210032160-3308https://doaj.org/article/79f3b4f4847d408eb286f3bdd273ccd42021-04-01T00:00:00Zhttp://doi.org/10.1103/PhysRevX.11.021003http://doi.org/10.1103/PhysRevX.11.021003https://doaj.org/toc/2160-3308Community detection methods attempt to divide a network into groups of nodes that share similar properties, thus revealing its large-scale structure. A major challenge when employing such methods is that they are often degenerate, typically yielding a complex landscape of competing answers. As an attempt to extract understanding from a population of alternative solutions, many methods exist to establish a consensus among them in the form of a single partition “point estimate” that summarizes the whole distribution. Here, we show that it is, in general, not possible to obtain a consistent answer from such point estimates when the underlying distribution is too heterogeneous. As an alternative, we provide a comprehensive set of methods designed to characterize and summarize complex populations of partitions in a manner that captures not only the existing consensus but also the dissensus between elements of the population. Our approach is able to model mixed populations of partitions, where multiple consensuses can coexist, representing different competing hypotheses for the network structure. We also show how our methods can be used to compare pairs of partitions, how they can be generalized to hierarchical divisions, and how they can be used to perform statistical model selection between competing hypotheses.Tiago P. PeixotoAmerican Physical SocietyarticlePhysicsQC1-999ENPhysical Review X, Vol 11, Iss 2, p 021003 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999
spellingShingle	Physics QC1-999 Tiago P. Peixoto Revealing Consensus and Dissensus between Network Partitions
description	Community detection methods attempt to divide a network into groups of nodes that share similar properties, thus revealing its large-scale structure. A major challenge when employing such methods is that they are often degenerate, typically yielding a complex landscape of competing answers. As an attempt to extract understanding from a population of alternative solutions, many methods exist to establish a consensus among them in the form of a single partition “point estimate” that summarizes the whole distribution. Here, we show that it is, in general, not possible to obtain a consistent answer from such point estimates when the underlying distribution is too heterogeneous. As an alternative, we provide a comprehensive set of methods designed to characterize and summarize complex populations of partitions in a manner that captures not only the existing consensus but also the dissensus between elements of the population. Our approach is able to model mixed populations of partitions, where multiple consensuses can coexist, representing different competing hypotheses for the network structure. We also show how our methods can be used to compare pairs of partitions, how they can be generalized to hierarchical divisions, and how they can be used to perform statistical model selection between competing hypotheses.
format	article
author	Tiago P. Peixoto
author_facet	Tiago P. Peixoto
author_sort	Tiago P. Peixoto
title	Revealing Consensus and Dissensus between Network Partitions
title_short	Revealing Consensus and Dissensus between Network Partitions
title_full	Revealing Consensus and Dissensus between Network Partitions
title_fullStr	Revealing Consensus and Dissensus between Network Partitions
title_full_unstemmed	Revealing Consensus and Dissensus between Network Partitions
title_sort	revealing consensus and dissensus between network partitions
publisher	American Physical Society
publishDate	2021
url	https://doaj.org/article/79f3b4f4847d408eb286f3bdd273ccd4
work_keys_str_mv	AT tiagoppeixoto revealingconsensusanddissensusbetweennetworkpartitions
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Revealing Consensus and Dissensus between Network Partitions

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