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Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. Th...

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Autores principales: Ho, Tung Manh, Nguyen, Ha Viet, Vuong, Thu-Trang, Dam, Quang-Minh, Pham, Hiep-Hung, Vuong, Quan-Hoang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590089/
https://www.ncbi.nlm.nih.gov/pubmed/28928958
http://dx.doi.org/10.12688/f1000research.12404.1
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author Ho, Tung Manh
Nguyen, Ha Viet
Vuong, Thu-Trang
Dam, Quang-Minh
Pham, Hiep-Hung
Vuong, Quan-Hoang
author_facet Ho, Tung Manh
Nguyen, Ha Viet
Vuong, Thu-Trang
Dam, Quang-Minh
Pham, Hiep-Hung
Vuong, Quan-Hoang
author_sort Ho, Tung Manh
collection PubMed
description Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals.
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spelling pubmed-55900892017-09-18 Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data Ho, Tung Manh Nguyen, Ha Viet Vuong, Thu-Trang Dam, Quang-Minh Pham, Hiep-Hung Vuong, Quan-Hoang F1000Res Research Article Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals. F1000Research 2017-08-24 /pmc/articles/PMC5590089/ /pubmed/28928958 http://dx.doi.org/10.12688/f1000research.12404.1 Text en Copyright: © 2017 Ho TM et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ho, Tung Manh
Nguyen, Ha Viet
Vuong, Thu-Trang
Dam, Quang-Minh
Pham, Hiep-Hung
Vuong, Quan-Hoang
Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data
title Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data
title_full Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data
title_fullStr Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data
title_full_unstemmed Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data
title_short Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data
title_sort exploring vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 scopus data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590089/
https://www.ncbi.nlm.nih.gov/pubmed/28928958
http://dx.doi.org/10.12688/f1000research.12404.1
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