How does author affiliation affect preprint citation count?
How does author affiliation affect preprint citation count?
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作者隶属关系如何影响预印本引用计数？
DOI：
10.1145/3529372.3530953
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Saier Tarek
中科院分区：
文献类型：
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作者：
Nishioka Chifumi;Faerber Michael;Saier Tarek
引文是科学话语的一个重要方面，对于量化研究者的科学影响力具有重要意义。以前的作品观察到，引用不仅基于纯学术贡献，而且基于非学术属性，如作者的从属关系或性别。这样就产生了引文偏差。现有的作品，但是，没有分析预印本方面的引用偏见，虽然他们在现代学术交流中发挥着越来越重要的作用。在本文中，我们调查预印本是否受到引文偏见方面的作者隶属关系。我们测量引用偏差bioRxiv预印本及其出版商版本在机构层面和国家层面，使用洛伦兹曲线和基尼系数。这使我们能够减轻混杂因素的影响，并查看与作者从属关系相关的引用偏见是否对预印本引用产生更大的影响。我们观察到一致较高的基尼系数预印本比出版商的版本。因此，我们可以确认引用偏差的存在，而且在预印本的情况下更严重。随着预印本的增加，基于隶属关系的引用偏见不仅对作者来说是一个重要的话题（例如，在决定引用什么时），而且还适用于使用引用进行科学影响量化的个人和机构（例如，资助机构基于引用计数来决定资助）。
Citing is an important aspect of scientific discourse and important for quantifying the scientific impact quantification of researchers. Previous works observed that citations are made not only based on the pure scholarly contributions but also based on non-scholarly attributes, such as the affiliation or gender of authors. In this way, citation bias is produced. Existing works, however, have not analyzed preprints with respect to citation bias, although they play an increasingly important role in modern scholarly communication. In this paper, we investigate whether preprints are affected by citation bias with respect to the author affiliation. We measure citation bias for bioRxiv preprints and their publisher versions at the institution level and country level, using the Lorenz curve and Gini coefficient. This allows us to mitigate the effects of confounding factors and see whether or not citation biases related to author affiliation have an increased effect on preprint citations. We observe consistent higher Gini coefficients for preprints than those for publisher versions. Thus, we can confirm that citation bias exists and that it is more severe in case of preprints. As preprints are on the rise, affiliation-based citation bias is, thus, an important topic not only for authors (e.g., when deciding what to cite), but also to people and institutions that use citations for scientific impact quantification (e.g., funding agencies deciding about funding based on citation counts).