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Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis
BACKGROUND: Team science research includes authors from various fields collaborating to publish their work on certain topics. Despite the numerous papers that discussed the ordering of author names and the contributions of authors to an article, no paper evaluated: (1).. the research achievement (RA...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249850/ https://www.ncbi.nlm.nih.gov/pubmed/32481321 http://dx.doi.org/10.1097/MD.0000000000020334 |
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author | Liu, Mei-Yuan Chou, Willy Chien, Tsair-Wei Kuo, Shu-Chun Yeh, Yu-Tsen Chou, Po-Hsin |
author_facet | Liu, Mei-Yuan Chou, Willy Chien, Tsair-Wei Kuo, Shu-Chun Yeh, Yu-Tsen Chou, Po-Hsin |
author_sort | Liu, Mei-Yuan |
collection | PubMed |
description | BACKGROUND: Team science research includes authors from various fields collaborating to publish their work on certain topics. Despite the numerous papers that discussed the ordering of author names and the contributions of authors to an article, no paper evaluated: (1).. the research achievement (RA) and (2).. the research domain (RD) for productive sole-author researchers. In addition, few researchers publish academic articles without co-author collaboration. Whether the bibliometric indexes (eg, h-/x-index) of sole-author researchers are higher than those of other types of multiple authors is required for comparison. We aimed to evaluate a productive author who published 114 sole-author articles with exceptional RA and RD in academics. METHODS: By searching the PubMed database (Pubmed.com), we used the keyword of (Taiwan[affiliation]) from 2016 to 2017 and downloaded 29,356 articles. One physician (Dr. Tseng from the field of Internal Medicine) who published 12 articles as a single author was selected. His articles and citations were searched in PubMed. A comparison of various types of author ordering placements was conducted using sensitivity analysis to inspect whether this sole author earns the highest metrics in RA. Social network analysis (SNA), Gini coefficient (GC), pyramid plot, and the Kano diagram were applied to gather the following data for visualization: (1).. the author collaborations and RA using x-index; (2).. the author's article-related journals frequently published in the past; (3).. the most influential medical subject heading (MeSH) using citation analysis to denote the author's RD. RESULTS: We observed that: (1).. DR Tseng contributed 114 sole-author articles in 140 publications (=81.4%) since 2002; (2).. the 100% sole-author scenario earned the highest h-/x-index; (3).. the author's RD includes epidemiology, complications, and metabolism with an exceptional GC (=0.55). CONCLUSIONS: The metrics on RA are high for the sole author studied. The author's RD can be denoted by the MeSH terms and measured by the GC. The author-weighted scheme is required for quantifying author credits in an article to evaluate the author's RA. Social network analysis incorporating the Kano diagrams provided insights into the relationships between actors (eg, coauthors, MeSH terms, or journals). The methods used in this study can be replicated to evaluate other productive studies on RA and RD in the future. |
format | Online Article Text |
id | pubmed-7249850 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-72498502020-06-15 Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis Liu, Mei-Yuan Chou, Willy Chien, Tsair-Wei Kuo, Shu-Chun Yeh, Yu-Tsen Chou, Po-Hsin Medicine (Baltimore) 4400 BACKGROUND: Team science research includes authors from various fields collaborating to publish their work on certain topics. Despite the numerous papers that discussed the ordering of author names and the contributions of authors to an article, no paper evaluated: (1).. the research achievement (RA) and (2).. the research domain (RD) for productive sole-author researchers. In addition, few researchers publish academic articles without co-author collaboration. Whether the bibliometric indexes (eg, h-/x-index) of sole-author researchers are higher than those of other types of multiple authors is required for comparison. We aimed to evaluate a productive author who published 114 sole-author articles with exceptional RA and RD in academics. METHODS: By searching the PubMed database (Pubmed.com), we used the keyword of (Taiwan[affiliation]) from 2016 to 2017 and downloaded 29,356 articles. One physician (Dr. Tseng from the field of Internal Medicine) who published 12 articles as a single author was selected. His articles and citations were searched in PubMed. A comparison of various types of author ordering placements was conducted using sensitivity analysis to inspect whether this sole author earns the highest metrics in RA. Social network analysis (SNA), Gini coefficient (GC), pyramid plot, and the Kano diagram were applied to gather the following data for visualization: (1).. the author collaborations and RA using x-index; (2).. the author's article-related journals frequently published in the past; (3).. the most influential medical subject heading (MeSH) using citation analysis to denote the author's RD. RESULTS: We observed that: (1).. DR Tseng contributed 114 sole-author articles in 140 publications (=81.4%) since 2002; (2).. the 100% sole-author scenario earned the highest h-/x-index; (3).. the author's RD includes epidemiology, complications, and metabolism with an exceptional GC (=0.55). CONCLUSIONS: The metrics on RA are high for the sole author studied. The author's RD can be denoted by the MeSH terms and measured by the GC. The author-weighted scheme is required for quantifying author credits in an article to evaluate the author's RA. Social network analysis incorporating the Kano diagrams provided insights into the relationships between actors (eg, coauthors, MeSH terms, or journals). The methods used in this study can be replicated to evaluate other productive studies on RA and RD in the future. Wolters Kluwer Health 2020-05-22 /pmc/articles/PMC7249850/ /pubmed/32481321 http://dx.doi.org/10.1097/MD.0000000000020334 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 4400 Liu, Mei-Yuan Chou, Willy Chien, Tsair-Wei Kuo, Shu-Chun Yeh, Yu-Tsen Chou, Po-Hsin Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis |
title | Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis |
title_full | Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis |
title_fullStr | Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis |
title_full_unstemmed | Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis |
title_short | Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis |
title_sort | evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: a bibliometric analysis |
topic | 4400 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249850/ https://www.ncbi.nlm.nih.gov/pubmed/32481321 http://dx.doi.org/10.1097/MD.0000000000020334 |
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