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Comment on the article: The state of social science research on COVID‑19

A well-written and interesting article was published on November 21, 2021. Future relevant studies, however, may be improved by implementing (1) a framework that outlines the overall research; (2) an author-weighted scheme (AWS) that accurately quantifies the contributions of entities to articles; a...

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Detalles Bibliográficos
Autores principales: Lin, Ju-Kuo, Chien, Tsair-Wei, Chou, Willy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9770560/
https://www.ncbi.nlm.nih.gov/pubmed/36573231
http://dx.doi.org/10.1007/s11192-022-04600-6
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author Lin, Ju-Kuo
Chien, Tsair-Wei
Chou, Willy
author_facet Lin, Ju-Kuo
Chien, Tsair-Wei
Chou, Willy
author_sort Lin, Ju-Kuo
collection PubMed
description A well-written and interesting article was published on November 21, 2021. Future relevant studies, however, may be improved by implementing (1) a framework that outlines the overall research; (2) an author-weighted scheme (AWS) that accurately quantifies the contributions of entities to articles; and (3) a more appropriate size for the nodes representing the proportional counts for each entity in social network analysis (SNA). VOSviewer was used to construct and visualize the scientometric networks and the relation-based analyses included three categories: (1) citation relations, (2) word cooccurrences, and (3) coauthorship relations. Nevertheless, the counts for each topical entity have not been consistently integrated. As a result, the nodes of the keyword co-occurrence network are large when compared to the number of connections between the entities or terms (i.e., the total number of relationships between co-occurring terms or entities). Additionally, all weighted counts in keywords (or the total link strength of a country/region) should equal the total number of documents (e.g., n = 9954 in that article). This would lead to biases in the calculation of publications (or citations) for entities, as is common in traditional SNA. This node illustrates a study framework and a couple of AWSs (i.e., equal and nonequal AWSs) to improve the article, and discusses the need to understand the requirement that the total centrality degree in SNA equals the total number of documents (or citations).
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spelling pubmed-97705602022-12-22 Comment on the article: The state of social science research on COVID‑19 Lin, Ju-Kuo Chien, Tsair-Wei Chou, Willy Scientometrics Article A well-written and interesting article was published on November 21, 2021. Future relevant studies, however, may be improved by implementing (1) a framework that outlines the overall research; (2) an author-weighted scheme (AWS) that accurately quantifies the contributions of entities to articles; and (3) a more appropriate size for the nodes representing the proportional counts for each entity in social network analysis (SNA). VOSviewer was used to construct and visualize the scientometric networks and the relation-based analyses included three categories: (1) citation relations, (2) word cooccurrences, and (3) coauthorship relations. Nevertheless, the counts for each topical entity have not been consistently integrated. As a result, the nodes of the keyword co-occurrence network are large when compared to the number of connections between the entities or terms (i.e., the total number of relationships between co-occurring terms or entities). Additionally, all weighted counts in keywords (or the total link strength of a country/region) should equal the total number of documents (e.g., n = 9954 in that article). This would lead to biases in the calculation of publications (or citations) for entities, as is common in traditional SNA. This node illustrates a study framework and a couple of AWSs (i.e., equal and nonequal AWSs) to improve the article, and discusses the need to understand the requirement that the total centrality degree in SNA equals the total number of documents (or citations). Springer International Publishing 2022-12-21 2023 /pmc/articles/PMC9770560/ /pubmed/36573231 http://dx.doi.org/10.1007/s11192-022-04600-6 Text en © Akadémiai Kiadó, Budapest, Hungary 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Lin, Ju-Kuo
Chien, Tsair-Wei
Chou, Willy
Comment on the article: The state of social science research on COVID‑19
title Comment on the article: The state of social science research on COVID‑19
title_full Comment on the article: The state of social science research on COVID‑19
title_fullStr Comment on the article: The state of social science research on COVID‑19
title_full_unstemmed Comment on the article: The state of social science research on COVID‑19
title_short Comment on the article: The state of social science research on COVID‑19
title_sort comment on the article: the state of social science research on covid‑19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9770560/
https://www.ncbi.nlm.nih.gov/pubmed/36573231
http://dx.doi.org/10.1007/s11192-022-04600-6
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