Topical Alignment in Online Social Systems

Understanding the dynamics of social interactions is crucial to comprehend human behavior. The emergence of online social media has enabled access to data regarding people relationships at a large scale. Twitter, specifically, is an information oriented network, with users sharing and consuming info...

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Detalles Bibliográficos
Autores: Cardoso, Felipe Maciel, Meloni, Sandro, Santanchè, André, Moreno, Yamir
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/189538
Acceso en línea:http://hdl.handle.net/10261/189538
Access Level:acceso abierto
Palabra clave:Social network analysis
Topical similarity
Data analysis
Computational social science
Twitter
Information networks
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spelling Topical Alignment in Online Social SystemsCardoso, Felipe MacielMeloni, SandroSantanchè, AndréMoreno, YamirSocial network analysisTopical similarityData analysisComputational social scienceTwitterInformation networksUnderstanding the dynamics of social interactions is crucial to comprehend human behavior. The emergence of online social media has enabled access to data regarding people relationships at a large scale. Twitter, specifically, is an information oriented network, with users sharing and consuming information. In this work, we study whether users tend to be in contact with people interested in similar topics, i.e., if they are topically aligned. To do so, we propose an approach based on the use of hashtags to extract information topics from Twitter messages and model users' interests. Our results show that, on average, users are connected with other users similar to them. Furthermore, we show that topical alignment provides interesting information that can eventually allow inferring users' connectivity. Our work, besides providing a way to assess the topical similarity of users, quantifies topical alignment among individuals, contributing to a better understanding of how complex social systems are structured.FC and AS acknowledges support from Microsoft, Santander, CAPES, CNPq, and FAPESP Project 2015/01587-0. SM acknowledges support from the Ramón y Cajal Program by MINECO, Spain. YM and SM acknowledge support from the Government of Aragón, Spain through a grant to the group FENOL, by MINECO and FEDER funds (grant FIS2017-87519-P) and by the European Commission FET-Proactive Project Multiplex (grant 317532). SM also acknowledge the Spanish State Research Agency, through the María de Maeztu Program for Units of Excellence in R&D (MDM-2017-0711).Peer reviewedFrontiers MediaAgencia Estatal de Investigación (España)Agencia Estatal de Investigación (España)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil)Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil)Fundação de Amparo à Pesquisa do Estado de São PauloMinisterio de Economía y Competitividad (España)Gobierno de AragónEuropean CommissionMinisterio de Ciencia, Innovación y Universidades (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]201920192019info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/189538reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#MDM-2017-0711/AEI/10.13039/501100011033info:eu-repo/grantAgreement/EC/FP7/317532FIS2017-87519-P/AEI/10.13039/501100011033info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FIS2017-87519-Pinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MDM-2017-0711https://doi.org/10.3389/fphy.2019.00058Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1895382026-05-22T06:33:51Z
dc.title.none.fl_str_mv Topical Alignment in Online Social Systems
title Topical Alignment in Online Social Systems
spellingShingle Topical Alignment in Online Social Systems
Cardoso, Felipe Maciel
Social network analysis
Topical similarity
Data analysis
Computational social science
Twitter
Information networks
title_short Topical Alignment in Online Social Systems
title_full Topical Alignment in Online Social Systems
title_fullStr Topical Alignment in Online Social Systems
title_full_unstemmed Topical Alignment in Online Social Systems
title_sort Topical Alignment in Online Social Systems
dc.creator.none.fl_str_mv Cardoso, Felipe Maciel
Meloni, Sandro
Santanchè, André
Moreno, Yamir
author Cardoso, Felipe Maciel
author_facet Cardoso, Felipe Maciel
Meloni, Sandro
Santanchè, André
Moreno, Yamir
author_role author
author2 Meloni, Sandro
Santanchè, André
Moreno, Yamir
author2_role author
author
author
dc.contributor.none.fl_str_mv Agencia Estatal de Investigación (España)
Agencia Estatal de Investigación (España)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil)
Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil)
Fundação de Amparo à Pesquisa do Estado de São Paulo
Ministerio de Economía y Competitividad (España)
Gobierno de Aragón
European Commission
Ministerio de Ciencia, Innovación y Universidades (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Social network analysis
Topical similarity
Data analysis
Computational social science
Twitter
Information networks
topic Social network analysis
Topical similarity
Data analysis
Computational social science
Twitter
Information networks
description Understanding the dynamics of social interactions is crucial to comprehend human behavior. The emergence of online social media has enabled access to data regarding people relationships at a large scale. Twitter, specifically, is an information oriented network, with users sharing and consuming information. In this work, we study whether users tend to be in contact with people interested in similar topics, i.e., if they are topically aligned. To do so, we propose an approach based on the use of hashtags to extract information topics from Twitter messages and model users' interests. Our results show that, on average, users are connected with other users similar to them. Furthermore, we show that topical alignment provides interesting information that can eventually allow inferring users' connectivity. Our work, besides providing a way to assess the topical similarity of users, quantifies topical alignment among individuals, contributing to a better understanding of how complex social systems are structured.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/189538
url http://hdl.handle.net/10261/189538
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
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#PLACEHOLDER_PARENT_METADATA_VALUE#
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#PLACEHOLDER_PARENT_METADATA_VALUE#
MDM-2017-0711/AEI/10.13039/501100011033
info:eu-repo/grantAgreement/EC/FP7/317532
FIS2017-87519-P/AEI/10.13039/501100011033
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FIS2017-87519-P
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MDM-2017-0711
https://doi.org/10.3389/fphy.2019.00058
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
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