Using mobile money data and call detail records to explore the risks of urban migration in Tanzania.
Call detail records
Exploitation
Machine learning
Migration
Mobile money
Tanzania
Vulnerability
Journal
EPJ data science
ISSN: 2193-1127
Titre abrégé: EPJ Data Sci
Pays: Germany
ID NLM: 101686785
Informations de publication
Date de publication:
2022
2022
Historique:
received:
21
12
2021
accepted:
14
04
2022
entrez:
16
5
2022
pubmed:
17
5
2022
medline:
17
5
2022
Statut:
ppublish
Résumé
Understanding what factors predict whether an urban migrant will end up in a deprived neighbourhood or not could help prevent the exploitation of vulnerable individuals. This study leveraged pseudonymized mobile money interactions combined with cell phone data to shed light on urban migration patterns and deprivation in Tanzania. Call detail records were used to identify individuals who migrated to Dar es Salaam, Tanzania's largest city. A street survey of the city's subwards was used to determine which individuals moved to more deprived areas. The online version contains supplementary material available at 10.1140/epjds/s13688-022-00340-y.
Identifiants
pubmed: 35571071
doi: 10.1140/epjds/s13688-022-00340-y
pii: 340
pmc: PMC9079216
doi:
Types de publication
Journal Article
Langues
eng
Pagination
28Informations de copyright
© The Author(s) 2022.
Déclaration de conflit d'intérêts
Competing interestsThe authors declare that they have no competing interests.
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