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Citing is an important aspect of scientific discourse and important forquantifying the scientific impact quantification of researchers. Previous worksobserved that citations are made not only based on the pure scholarlycontributions but also based on non-scholarly attributes, such as theaffiliation or gender of authors. In this way, citation bias is produced.Existing works, however, have not analyzed preprints with respect to citationbias, although they play an increasingly important role in modern scholarlycommunication. In this paper, we investigate whether preprints are affected bycitation bias with respect to the author affiliation. We measure citation biasfor bioRxiv preprints and their publisher versions at the institution level andcountry level, using the Lorenz curve and Gini coefficient. This allows us tomitigate the effects of confounding factors and see whether or not citationbiases related to author affiliation have an increased effect on preprintcitations. We observe consistent higher Gini coefficients for preprints thanthose for publisher versions. Thus, we can confirm that citation bias existsand 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 forauthors (e.g., when deciding what to cite), but also to people and institutionsthat use citations for scientific impact quantification (e.g., funding agenciesdeciding about funding based on citation counts).

How Does Author Affiliation Affect Preprint Citation Count? Analyzing Citation Bias at the Institution and Country Level