Community detection in multiplex networks

A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures, and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic.

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Main Authors: Magnani, Matteo, Hanteer, Obaida, Interdonato, Roberto, Rossi, Luca, Tagarelli, Andrea
Format: article biblioteca
Language:eng
Subjects:U10 - Informatique, mathématiques et statistiques, C30 - Documentation et information, analyse de réseau, réseau, commune, analyse de données, taxonomie (gestion de l'information), http://aims.fao.org/aos/agrovoc/c_5144, http://aims.fao.org/aos/agrovoc/c_50266, http://aims.fao.org/aos/agrovoc/c_1786, http://aims.fao.org/aos/agrovoc/c_15962, http://aims.fao.org/aos/agrovoc/c_49906,
Online Access:http://agritrop.cirad.fr/598423/
http://agritrop.cirad.fr/598423/1/3444688.pdf
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spelling dig-cirad-fr-5984232024-04-24T11:45:15Z http://agritrop.cirad.fr/598423/ http://agritrop.cirad.fr/598423/ Community detection in multiplex networks. Magnani Matteo, Hanteer Obaida, Interdonato Roberto, Rossi Luca, Tagarelli Andrea. 2021. ACM Computing Surveys, 5 (3):48, 35 p.https://doi.org/10.1145/3444688 <https://doi.org/10.1145/3444688> Community detection in multiplex networks Magnani, Matteo Hanteer, Obaida Interdonato, Roberto Rossi, Luca Tagarelli, Andrea eng 2021 ACM Computing Surveys U10 - Informatique, mathématiques et statistiques C30 - Documentation et information analyse de réseau réseau commune analyse de données taxonomie (gestion de l'information) http://aims.fao.org/aos/agrovoc/c_5144 http://aims.fao.org/aos/agrovoc/c_50266 http://aims.fao.org/aos/agrovoc/c_1786 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_49906 A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures, and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/598423/1/3444688.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1145/3444688 10.1145/3444688 info:eu-repo/semantics/altIdentifier/doi/10.1145/3444688 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1145/3444688 info:eu-repo/semantics/reference/purl/https://bitbucket.org/uuinfolab/20csur/src/master/
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
analyse de réseau
réseau
commune
analyse de données
taxonomie (gestion de l'information)
http://aims.fao.org/aos/agrovoc/c_5144
http://aims.fao.org/aos/agrovoc/c_50266
http://aims.fao.org/aos/agrovoc/c_1786
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_49906
U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
analyse de réseau
réseau
commune
analyse de données
taxonomie (gestion de l'information)
http://aims.fao.org/aos/agrovoc/c_5144
http://aims.fao.org/aos/agrovoc/c_50266
http://aims.fao.org/aos/agrovoc/c_1786
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_49906
spellingShingle U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
analyse de réseau
réseau
commune
analyse de données
taxonomie (gestion de l'information)
http://aims.fao.org/aos/agrovoc/c_5144
http://aims.fao.org/aos/agrovoc/c_50266
http://aims.fao.org/aos/agrovoc/c_1786
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_49906
U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
analyse de réseau
réseau
commune
analyse de données
taxonomie (gestion de l'information)
http://aims.fao.org/aos/agrovoc/c_5144
http://aims.fao.org/aos/agrovoc/c_50266
http://aims.fao.org/aos/agrovoc/c_1786
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_49906
Magnani, Matteo
Hanteer, Obaida
Interdonato, Roberto
Rossi, Luca
Tagarelli, Andrea
Community detection in multiplex networks
description A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures, and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic.
format article
topic_facet U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
analyse de réseau
réseau
commune
analyse de données
taxonomie (gestion de l'information)
http://aims.fao.org/aos/agrovoc/c_5144
http://aims.fao.org/aos/agrovoc/c_50266
http://aims.fao.org/aos/agrovoc/c_1786
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_49906
author Magnani, Matteo
Hanteer, Obaida
Interdonato, Roberto
Rossi, Luca
Tagarelli, Andrea
author_facet Magnani, Matteo
Hanteer, Obaida
Interdonato, Roberto
Rossi, Luca
Tagarelli, Andrea
author_sort Magnani, Matteo
title Community detection in multiplex networks
title_short Community detection in multiplex networks
title_full Community detection in multiplex networks
title_fullStr Community detection in multiplex networks
title_full_unstemmed Community detection in multiplex networks
title_sort community detection in multiplex networks
url http://agritrop.cirad.fr/598423/
http://agritrop.cirad.fr/598423/1/3444688.pdf
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AT interdonatoroberto communitydetectioninmultiplexnetworks
AT rossiluca communitydetectioninmultiplexnetworks
AT tagarelliandrea communitydetectioninmultiplexnetworks
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