Suppr超能文献

致谢中提到的已确认学者数据集。

Dataset of identified scholars mentioned in acknowledgement statements.

机构信息

University of Tsukuba, Graduate School of Science and Technology, Ibaraki, 305-8573, Japan.

University of Tsukuba, Faculty of Engineering, Information and Systems, Ibaraki, 305-8573, Japan.

出版信息

Sci Data. 2022 Aug 1;9(1):461. doi: 10.1038/s41597-022-01585-y.

Abstract

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.

摘要

致谢部分体现了学者在研究中的合作关系。虽然合著者和引文通常以格式化的文献计量数据库形式呈现,但由于被致谢者的信息出现在论文的陈述部分,因此很难识别。我们通过参考存储在 Microsoft Academic Graph(MAG)中的合著者和引文关系,识别发表在开放获取期刊上的论文中出现的被致谢学者。因此,构建的数据集与 MAG 兼容,这加速并扩展了致谢作为与合作和引文分析类似的学术关系数据源。此外,实现的代码是公开可用的;因此,它可以应用于其他研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23be/9343655/42a51d2d7b8e/41597_2022_1585_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验