The anatomy of a population-scale social network.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
06 06 2023
06 06 2023
Historique:
received:
12
01
2023
accepted:
01
06
2023
medline:
8
6
2023
pubmed:
7
6
2023
entrez:
6
6
2023
Statut:
epublish
Résumé
Large-scale human social network structure is typically inferred from digital trace samples of online social media platforms or mobile communication data. Instead, here we investigate the social network structure of a complete population, where people are connected by high-quality links sourced from administrative registers of family, household, work, school, and next-door neighbors. We examine this multilayer social opportunity structure through three common concepts in network analysis: degree, closure, and distance. Findings present how particular network layers contribute to presumably universal scale-free and small-world properties of networks. Furthermore, we suggest a novel measure of excess closure and apply this in a life-course perspective to show how the social opportunity structure of individuals varies along age, socio-economic status, and education level.
Identifiants
pubmed: 37280385
doi: 10.1038/s41598-023-36324-9
pii: 10.1038/s41598-023-36324-9
pmc: PMC10244344
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
9209Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2023. The Author(s).
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