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De-anonymization of authors through arXiv submissions during double-blind review

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arxiv 2007.00177 v1 pith:B5JXUR2A submitted 2020-07-01 cs.CY cs.IRcs.LG

De-anonymization of authors through arXiv submissions during double-blind review

classification cs.CY cs.IRcs.LG
keywords reviewarxivauthorsscoresacceptancedouble-blindreputationcorrelation
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In this paper, we investigate the effects of releasing arXiv preprints of papers that are undergoing a double-blind review process. In particular, we ask the following research question: What is the relation between de-anonymization of authors through arXiv preprints and acceptance of a research paper at a (nominally) double-blind venue? Under two conditions: papers that are released on arXiv before the review phase and papers that are not, we examine the correlation between the reputation of their authors with the review scores and acceptance decisions. By analyzing a dataset of ICLR 2020 and ICLR 2019 submissions (n=5050), we find statistically significant evidence of positive correlation between percentage acceptance and papers with high reputation released on arXiv. In order to understand this observed association better, we perform additional analyses based on self-specified confidence scores of reviewers and observe that less confident reviewers are more likely to assign high review scores to papers with well known authors and low review scores to papers with less known authors, where reputation is quantified in terms of number of Google Scholar citations. We emphasize upfront that our results are purely correlational and we neither can nor intend to make any causal claims. A blog post accompanying the paper and our scraping code will be linked in the project website https://sites.google.com/view/deanon-arxiv/home

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Cited by 1 Pith paper

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  1. Bias at the Borderline: Who Gets the Benefit of the Doubt in Peer Review?

    cs.DL 2026-07 conditional novelty 8.0

    At ICLR, equally scored borderline papers from outside top-25 institutions are accepted less often, a gap concentrated in preprint-identifiable submissions; outcome tests find no evidence of a higher bar.