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 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| bookPart_95227.pdf | 1,21 MB | Adobe PDF | View/Open |
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