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Spatial social network research: a bibliometric analysis

A restless and dynamic intellectual landscape has taken hold in the field of spatial social network studies, given the increasingly attention towards fine-scale human dynamics in this urbanizing and mobile world. The measuring parameters of such dramatic growth of the literature include scientific o...

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Detalles Bibliográficos
Autores principales: Wu, Ling, Peng, Qiong, Lemke, Michael, Hu, Tao, Gong, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115482/
https://www.ncbi.nlm.nih.gov/pubmed/37096207
http://dx.doi.org/10.1007/s43762-022-00045-y
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author Wu, Ling
Peng, Qiong
Lemke, Michael
Hu, Tao
Gong, Xi
author_facet Wu, Ling
Peng, Qiong
Lemke, Michael
Hu, Tao
Gong, Xi
author_sort Wu, Ling
collection PubMed
description A restless and dynamic intellectual landscape has taken hold in the field of spatial social network studies, given the increasingly attention towards fine-scale human dynamics in this urbanizing and mobile world. The measuring parameters of such dramatic growth of the literature include scientific outputs, domain categories, major journals, countries, institutions, and frequently used keywords. The research in the field has been characterized by fast development of relevant scholarly articles and growing collaboration among and across institutions. The Journal of Economic Geography, Annals of the Association of American Geographers, and Urban Studies ranked first, second, and third, respectively, according to average citations. The United States, United Kingdom, and China were the countries that yielded the most published studies in the field. The number of international collaborative studies published in non-native English-speaking countries (such as France, Italy, and the Netherlands) were higher than native English-speaking countries. Wuhan University, the University of Oxford, and Harvard University were the universities that published the most in the field. “Twitter”, “big data”, “networks”, “spatial analysis”, and “social capital” have been the major keywords over the past 20 years. At the same time, the keywords such as “social media”, “Twitter”, “big data”, “geography”, “China”, “human mobility”, “machine learning”, “GIS”, “location-based social networks”, “clustering”, “data mining”, and “location-based services” have attracted increasing attention in that same time frame, indicating the future research trends.
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spelling pubmed-101154822023-04-20 Spatial social network research: a bibliometric analysis Wu, Ling Peng, Qiong Lemke, Michael Hu, Tao Gong, Xi Comput Urban Sci Review A restless and dynamic intellectual landscape has taken hold in the field of spatial social network studies, given the increasingly attention towards fine-scale human dynamics in this urbanizing and mobile world. The measuring parameters of such dramatic growth of the literature include scientific outputs, domain categories, major journals, countries, institutions, and frequently used keywords. The research in the field has been characterized by fast development of relevant scholarly articles and growing collaboration among and across institutions. The Journal of Economic Geography, Annals of the Association of American Geographers, and Urban Studies ranked first, second, and third, respectively, according to average citations. The United States, United Kingdom, and China were the countries that yielded the most published studies in the field. The number of international collaborative studies published in non-native English-speaking countries (such as France, Italy, and the Netherlands) were higher than native English-speaking countries. Wuhan University, the University of Oxford, and Harvard University were the universities that published the most in the field. “Twitter”, “big data”, “networks”, “spatial analysis”, and “social capital” have been the major keywords over the past 20 years. At the same time, the keywords such as “social media”, “Twitter”, “big data”, “geography”, “China”, “human mobility”, “machine learning”, “GIS”, “location-based social networks”, “clustering”, “data mining”, and “location-based services” have attracted increasing attention in that same time frame, indicating the future research trends. Springer Nature Singapore 2022-07-09 2022 /pmc/articles/PMC10115482/ /pubmed/37096207 http://dx.doi.org/10.1007/s43762-022-00045-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review
Wu, Ling
Peng, Qiong
Lemke, Michael
Hu, Tao
Gong, Xi
Spatial social network research: a bibliometric analysis
title Spatial social network research: a bibliometric analysis
title_full Spatial social network research: a bibliometric analysis
title_fullStr Spatial social network research: a bibliometric analysis
title_full_unstemmed Spatial social network research: a bibliometric analysis
title_short Spatial social network research: a bibliometric analysis
title_sort spatial social network research: a bibliometric analysis
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115482/
https://www.ncbi.nlm.nih.gov/pubmed/37096207
http://dx.doi.org/10.1007/s43762-022-00045-y
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