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Dataset of identified scholars mentioned in acknowledgement statements
Acknowledgements represent scholars’ relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We iden...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343655/ https://www.ncbi.nlm.nih.gov/pubmed/35915099 http://dx.doi.org/10.1038/s41597-022-01585-y |
_version_ | 1784761036481495040 |
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author | Kusumegi, Keigo Sano, Yukie |
author_facet | Kusumegi, Keigo Sano, Yukie |
author_sort | Kusumegi, Keigo |
collection | PubMed |
description | Acknowledgements represent scholars’ relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We identify acknowledged scholars who appeared in papers published in open-access journals by referring to the co-author and citation relationships stored in the Microsoft Academic Graph (MAG). Therefore, the constructed dataset is compatible with MAG, which accelerates and expands the acknowledgements as a data source of scholarly relationships similar to collaboration and citation analysis. Moreover, the implemented code is publicly available; thus, it can be applied in other studies. |
format | Online Article Text |
id | pubmed-9343655 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93436552022-08-03 Dataset of identified scholars mentioned in acknowledgement statements Kusumegi, Keigo Sano, Yukie Sci Data Data Descriptor Acknowledgements represent scholars’ relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We identify acknowledged scholars who appeared in papers published in open-access journals by referring to the co-author and citation relationships stored in the Microsoft Academic Graph (MAG). Therefore, the constructed dataset is compatible with MAG, which accelerates and expands the acknowledgements as a data source of scholarly relationships similar to collaboration and citation analysis. Moreover, the implemented code is publicly available; thus, it can be applied in other studies. Nature Publishing Group UK 2022-08-01 /pmc/articles/PMC9343655/ /pubmed/35915099 http://dx.doi.org/10.1038/s41597-022-01585-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Kusumegi, Keigo Sano, Yukie Dataset of identified scholars mentioned in acknowledgement statements |
title | Dataset of identified scholars mentioned in acknowledgement statements |
title_full | Dataset of identified scholars mentioned in acknowledgement statements |
title_fullStr | Dataset of identified scholars mentioned in acknowledgement statements |
title_full_unstemmed | Dataset of identified scholars mentioned in acknowledgement statements |
title_short | Dataset of identified scholars mentioned in acknowledgement statements |
title_sort | dataset of identified scholars mentioned in acknowledgement statements |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343655/ https://www.ncbi.nlm.nih.gov/pubmed/35915099 http://dx.doi.org/10.1038/s41597-022-01585-y |
work_keys_str_mv | AT kusumegikeigo datasetofidentifiedscholarsmentionedinacknowledgementstatements AT sanoyukie datasetofidentifiedscholarsmentionedinacknowledgementstatements |