Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/28152
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Campo DCValorIdioma
dc.contributor.authorFonseca, A. F.-
dc.contributor.authorLouçã, L.-
dc.contributor.editorManuel João Ramos-
dc.contributor.editorPedro Neto-
dc.contributor.editorGiulia Daniele-
dc.date.accessioned2023-03-03T09:04:30Z-
dc.date.available2023-03-03T09:04:30Z-
dc.date.issued2022-
dc.identifier.citationFonseca, A. F., & Louça, J. (2022). Network-based approaches for studying migrations. EM Manuel João Ramos, Pedro Neto, & Giulia Daniele (Eds.). Border crossings in and out of Europe (pp. 200-231). Centro de Estudos Internacionais do Instituto Universitário de Lisboa (CEI-Iscte).-
dc.identifier.isbn978-989-781-719-9-
dc.identifier.urihttp://hdl.handle.net/10071/28152-
dc.description.abstractRecently the United Nations released an updated version of its Global Migration Dataset (UNHCR, 2017). We applied network science methods in order to uncover structural patterns within global migration flows observed in these data. Results revealed strong patterns in global migration, resulting from geographical and cultural constraints. Specifically, the Louvain community detection algorithm aggregated countries according with their linguistic, political, and economic affinities. Additionally, the Infomap community detection algorithm explored the distance and geography factors influencing migration flows. Both results weighted flow dynamics over a migration dataset related to the period from 1995 to 2017.eng
dc.language.isoeng-
dc.publisherCentro de Estudos Internacionais do Instituto Universitário de Lisboa (CEI-Iscte)-
dc.relation.ispartofBorder crossings in and out of Europe-
dc.rightsopenAccess-
dc.subjectRefugiados -- Refugeeseng
dc.subjectGlobal flowseng
dc.subjectAlgorithms network scienceeng
dc.titleNetwork-based approaches for studying migrationseng
dc.typebookPart-
dc.event.locationLisboaeng
dc.pagination200 - 231-
dc.peerreviewedyes-
dc.date.updated2023-03-03T09:03:44Z-
dc.description.versioninfo:eu-repo/semantics/publishedVersion-
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-95227-
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