Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/28152
Author(s): Fonseca, A. F.
Louçã, L.
Editor: Manuel João Ramos
Pedro Neto
Giulia Daniele
Date: 2022
Title: Network-based approaches for studying migrations
Book title/volume: Border crossings in and out of Europe
Pages: 200 - 231
Reference: Fonseca, 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).
ISBN: 978-989-781-719-9
Keywords: Refugiados -- Refugees
Global flows
Algorithms network science
Abstract: Recently 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.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-CLN - Capítulos de livros nacionais

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