Demarcating geographic regions using community detection in commuting networks with significant self-loops.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2020
2020
Historique:
received:
31
05
2019
accepted:
12
03
2020
entrez:
30
4
2020
pubmed:
30
4
2020
medline:
7
7
2020
Statut:
epublish
Résumé
We develop a method to identify statistically significant communities in a weighted network with a high proportion of self-looping weights. We use this method to find overlapping agglomerations of U.S. counties by representing inter-county commuting as a weighted network. We identify three types of communities; non-nodal, nodal and monads, which correspond to different types of regions. The results suggest that traditional regional delineations that rely on ad hoc thresholds do not account for important and pervasive connections that extend far beyond expected metropolitan boundaries or megaregions.
Identifiants
pubmed: 32348311
doi: 10.1371/journal.pone.0230941
pii: PONE-D-19-14845
pmc: PMC7190107
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0230941Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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