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Geographical Network Analysis

As the volume of digital data is growing exponentially and computational methods are advancing rapidly, network analysis is an increasingly important analytical tool to understand social life. This paper revisits the rich history of network analysis in geography and uses insights from that history t...

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Detalles Bibliográficos
Autores principales: Uitermark, Justus, van Meeteren, Michiel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459335/
https://www.ncbi.nlm.nih.gov/pubmed/34594058
http://dx.doi.org/10.1111/tesg.12480
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author Uitermark, Justus
van Meeteren, Michiel
author_facet Uitermark, Justus
van Meeteren, Michiel
author_sort Uitermark, Justus
collection PubMed
description As the volume of digital data is growing exponentially and computational methods are advancing rapidly, network analysis is an increasingly important analytical tool to understand social life. This paper revisits the rich history of network analysis in geography and uses insights from that history to review contemporary computational social science. Based on that analysis, we synthesize the distinctive qualities of what we term geographical network analysis. Geographical network analysis presumes that networks are situated, construed through meaning, and reflect power relations. Instead of pursuing parsimonious explanations or universal theories, geographical network analysis strives to understand how uneven networks develop across space and within place through a constant back and forth between abstraction and contextualization. Drawing on the articles in this special issue, this paper illustrates how geographical network analysis can be put to work.
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spelling pubmed-84593352021-09-28 Geographical Network Analysis Uitermark, Justus van Meeteren, Michiel Tijdschr Econ Soc Geogr Special Issue: Reviving network analysis in geography As the volume of digital data is growing exponentially and computational methods are advancing rapidly, network analysis is an increasingly important analytical tool to understand social life. This paper revisits the rich history of network analysis in geography and uses insights from that history to review contemporary computational social science. Based on that analysis, we synthesize the distinctive qualities of what we term geographical network analysis. Geographical network analysis presumes that networks are situated, construed through meaning, and reflect power relations. Instead of pursuing parsimonious explanations or universal theories, geographical network analysis strives to understand how uneven networks develop across space and within place through a constant back and forth between abstraction and contextualization. Drawing on the articles in this special issue, this paper illustrates how geographical network analysis can be put to work. John Wiley and Sons Inc. 2021-08-04 2021-09 /pmc/articles/PMC8459335/ /pubmed/34594058 http://dx.doi.org/10.1111/tesg.12480 Text en © 2021 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Special Issue: Reviving network analysis in geography
Uitermark, Justus
van Meeteren, Michiel
Geographical Network Analysis
title Geographical Network Analysis
title_full Geographical Network Analysis
title_fullStr Geographical Network Analysis
title_full_unstemmed Geographical Network Analysis
title_short Geographical Network Analysis
title_sort geographical network analysis
topic Special Issue: Reviving network analysis in geography
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459335/
https://www.ncbi.nlm.nih.gov/pubmed/34594058
http://dx.doi.org/10.1111/tesg.12480
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