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The journey of F1000Research since inception: through bibliometric analysis
Background: Bibliometric analysis is an approach adopted by researchers to understand the various analytics such as year-wise publications, their citations, most impactful authors and their contributions, identification of emerging keywords, multiple themes (niche, motor, basic, and emerging or decl...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238821/ https://www.ncbi.nlm.nih.gov/pubmed/37274828 http://dx.doi.org/10.12688/f1000research.134244.2 |
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author | Kumar, Dilip Shandilya, Abhinav Kumar Srivastava, Sandeep |
author_facet | Kumar, Dilip Shandilya, Abhinav Kumar Srivastava, Sandeep |
author_sort | Kumar, Dilip |
collection | PubMed |
description | Background: Bibliometric analysis is an approach adopted by researchers to understand the various analytics such as year-wise publications, their citations, most impactful authors and their contributions, identification of emerging keywords, multiple themes (niche, motor, basic, and emerging or declining) etc. F1000Research is one of the Q1 category journals that publishes articles in various domains, but a detailed journal analysis is yet to be done. Methods: This study is an effort to extract the F1000Research journey information through bibliometric analysis using VOS-viewer and Biblioshiny (R-studio) interface. The F1000Research journal started its journey in 2012; since then, 5767 articles have been published until the end of 2022. Most of the published articles are from medical science, covering Biochemistry, Genetics & Molecular Biology, Immunology & Pharmacology, Toxicology & Pharmaceutics. To understand the research journey, various analyses such as publication & citation trends, leading authors, institutions, countries, most frequent keywords, bibliographic coupling between authors, countries and documents, emerging research themes, and trending keywords were performed. Results: The United States is the biggest contributor, and COVID-19 is the most commonly occurred keyword. Conclusions: The present study may help future researchers to understand the emerging medical science domain. It will also help the editors and journal to focus more on developing or emerging areas and to understand their importance towards society. Future researchers can contribute their quality research studies, focusing on emerging themes. These authors’ research can guide future researchers to develop their research area around the most impacted articles. They can collaborate with them to bring that emerging theme forward. |
format | Online Article Text |
id | pubmed-10238821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-102388212023-06-04 The journey of F1000Research since inception: through bibliometric analysis Kumar, Dilip Shandilya, Abhinav Kumar Srivastava, Sandeep F1000Res Research Article Background: Bibliometric analysis is an approach adopted by researchers to understand the various analytics such as year-wise publications, their citations, most impactful authors and their contributions, identification of emerging keywords, multiple themes (niche, motor, basic, and emerging or declining) etc. F1000Research is one of the Q1 category journals that publishes articles in various domains, but a detailed journal analysis is yet to be done. Methods: This study is an effort to extract the F1000Research journey information through bibliometric analysis using VOS-viewer and Biblioshiny (R-studio) interface. The F1000Research journal started its journey in 2012; since then, 5767 articles have been published until the end of 2022. Most of the published articles are from medical science, covering Biochemistry, Genetics & Molecular Biology, Immunology & Pharmacology, Toxicology & Pharmaceutics. To understand the research journey, various analyses such as publication & citation trends, leading authors, institutions, countries, most frequent keywords, bibliographic coupling between authors, countries and documents, emerging research themes, and trending keywords were performed. Results: The United States is the biggest contributor, and COVID-19 is the most commonly occurred keyword. Conclusions: The present study may help future researchers to understand the emerging medical science domain. It will also help the editors and journal to focus more on developing or emerging areas and to understand their importance towards society. Future researchers can contribute their quality research studies, focusing on emerging themes. These authors’ research can guide future researchers to develop their research area around the most impacted articles. They can collaborate with them to bring that emerging theme forward. F1000 Research Limited 2023-06-07 /pmc/articles/PMC10238821/ /pubmed/37274828 http://dx.doi.org/10.12688/f1000research.134244.2 Text en Copyright: © 2023 Kumar D et al. https://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 Kumar, Dilip Shandilya, Abhinav Kumar Srivastava, Sandeep The journey of F1000Research since inception: through bibliometric analysis |
title | The journey of F1000Research since inception: through bibliometric analysis |
title_full | The journey of F1000Research since inception: through bibliometric analysis |
title_fullStr | The journey of F1000Research since inception: through bibliometric analysis |
title_full_unstemmed | The journey of F1000Research since inception: through bibliometric analysis |
title_short | The journey of F1000Research since inception: through bibliometric analysis |
title_sort | journey of f1000research since inception: through bibliometric analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238821/ https://www.ncbi.nlm.nih.gov/pubmed/37274828 http://dx.doi.org/10.12688/f1000research.134244.2 |
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