Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/340067
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampCardoso, Felipe Maciel-
dc.contributor.authorunicampSantanchè, André-
dc.typeArtigopt_BR
dc.titleTopical alignment in online social systemspt_BR
dc.contributor.authorMaciel Cardoso, Felipe-
dc.contributor.authorMeloni, Sandro-
dc.contributor.authorSantanche, Andre-
dc.contributor.authorMoreno, Yamir-
dc.subjectRedes sociais - Análisept_BR
dc.subject.otherlanguageSocial networks - Analysispt_BR
dc.description.abstractUnderstanding 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.pt_BR
dc.relation.ispartofFrontiers in physicspt_BR
dc.publisher.cityLausannept_BR
dc.publisher.countrySuíçapt_BR
dc.publisherFrontiers Mediapt_BR
dc.date.issued2019-
dc.date.monthofcirculationApr.pt_BR
dc.language.isoengpt_BR
dc.description.volume7pt_BR
dc.rightsAbertopt_BR
dc.sourceWOSpt_BR
dc.identifier.eissn2296-424Xpt_BR
dc.identifier.doi10.3389/fphy.2019.00058pt_BR
dc.identifier.urlhttps://www.frontiersin.org/articles/10.3389/fphy.2019.00058/fullpt_BR
dc.description.sponsorshipCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQpt_BR
dc.description.sponsorshipCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESpt_BR
dc.description.sponsorshipFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPpt_BR
dc.description.sponsordocumentnumberSem informaçãopt_BR
dc.description.sponsordocumentnumberSem informaçãopt_BR
dc.description.sponsordocumentnumber2015/01587-0pt_BR
dc.date.available2020-05-04T19:04:21Z-
dc.date.accessioned2020-05-04T19:04:21Z-
dc.description.provenanceSubmitted by Bruna Maria Campos da Cunha (bcampos@unicamp.br) on 2020-05-04T19:04:21Z No. of bitstreams: 0. Added 1 bitstream(s) on 2020-08-27T19:16:15Z : No. of bitstreams: 1 000465043000001.pdf: 2847362 bytes, checksum: f90fb5e0638ff0d7124b8e4794599956 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-05-04T19:04:21Z (GMT). No. of bitstreams: 0 Previous issue date: 2019en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/340067-
dc.contributor.departmentSem informaçãopt_BR
dc.contributor.departmentDepartamento de Sistemas de Informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordSocial network analysispt_BR
dc.subject.keywordTopical similaritypt_BR
dc.subject.keywordData analysispt_BR
dc.subject.keywordComputational social sciencept_BR
dc.subject.keywordTwitterpt_BR
dc.subject.keywordInformation networkspt_BR
dc.identifier.source000465043000001pt_BR
dc.creator.orcidSem informaçãopt_BR
dc.creator.orcidorcid.org/0000-0002-1756-4852pt_BR
dc.type.formArtigo de pesquisapt_BR
dc.identifier.articleid58pt_BR
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