Migration and commuting interactions fields: a new geography with community detection algorithm?
The objective is to refresh the geography of Belgium using interactions between places by means of a community detection algorithm (Louvain Method) inspired by Complex theory and Data Sciences. Places that are tightly related are optimally clustered into communities, leading to a new and optimal partition of Belgium. Migrations and commuting movements (Census11) are here analysed. We obtain a mosaic of “interaction fields†that are here interpreted in terms of methodological choices, human and urban geography as well as Belgian political dilemmas. They give the opportunity to remind that re... Mehr ...
Verfasser: | |
---|---|
Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2017 |
Verlag/Hrsg.: |
OpenEdition
|
Schlagwörter: | community detection / interaction fields / migration / commuting / provinces / Belgium |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26982066 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/2078.1/214172 |
The objective is to refresh the geography of Belgium using interactions between places by means of a community detection algorithm (Louvain Method) inspired by Complex theory and Data Sciences. Places that are tightly related are optimally clustered into communities, leading to a new and optimal partition of Belgium. Migrations and commuting movements (Census11) are here analysed. We obtain a mosaic of “interaction fields†that are here interpreted in terms of methodological choices, human and urban geography as well as Belgian political dilemmas. They give the opportunity to remind that researchers have to control the impact of their methodological choices and that each type of data leads to a different geographical partitioning, with one major unexpected common spatial feature in Belgium: the pre-eminence of the provincial borders. This perfectly fits with current political questioning.