Cite-seeing and Reviewing: A Study on Citation Bias in Peer Review

TL;DR

This study investigates whether citing a reviewer's own work influences their review scores, finding evidence of citation bias that can significantly impact paper evaluations in peer review.

Contribution

It provides the first empirical evidence of citation bias in peer review, quantifying its effect size and demonstrating its presence in top machine learning and economics conferences.

Findings

Citing a reviewer's work increases the likelihood of a higher review score.

The expected score increase from citation bias is approximately 0.23 on a 5-point scale.

Citation bias can improve a paper’s review score by about 11% on average.

Abstract

Citations play an important role in researchers' careers as a key factor in evaluation of scientific impact. Many anecdotes advice authors to exploit this fact and cite prospective reviewers to try obtaining a more positive evaluation for their submission. In this work, we investigate if such a citation bias actually exists: Does the citation of a reviewer's own work in a submission cause them to be positively biased towards the submission? In conjunction with the review process of two flagship conferences in machine learning and algorithmic economics, we execute an observational study to test for citation bias in peer review. In our analysis, we carefully account for various confounding factors such as paper quality and reviewer expertise, and apply different modeling techniques to alleviate concerns regarding the model mismatch. Overall, our analysis involves 1,314 papers and 1,717 reviewers and detects citation bias in both venues we consider. In terms of the effect size, by citing a reviewer's work, a submission has a non-trivial chance of getting a higher score from the reviewer: an expected increase in the score is approximately 0.23 on a 5-point Likert item. For reference, a one-point increase of a score by a single reviewer improves the position of a submission by 11% on average.