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How does author affiliation affect preprint citation count? Analyzing citation bias at the institution and country level

Nishioka, Chifumi; Färber, Michael ORCID iD icon 1; Saier, Tarek 1
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

Abstract:

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. ... mehr


Volltext §
DOI: 10.5445/IR/1000148639
Veröffentlicht am 17.10.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Forschungsbericht/Preprint
Publikationsdatum 04.05.2022
Sprache Englisch
Identifikator KITopen-ID: 1000148639
Verlag arxiv
Umfang 8 S.
Nachgewiesen in Dimensions
arXiv
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