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Cite-seeing and reviewing: A study on citation bias in peer review

Author

Listed:
  • Stelmakh, Ivan
  • Rastogi, Charvi
  • Liu, Ryan
  • Chawla, Shuchi
  • Echenique, Federico
  • Shah, Nihar B

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.

Suggested Citation

  • Stelmakh, Ivan & Rastogi, Charvi & Liu, Ryan & Chawla, Shuchi & Echenique, Federico & Shah, Nihar B, 2023. "Cite-seeing and reviewing: A study on citation bias in peer review," Department of Economics, Working Paper Series qt3883h8j1, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    • Handle: RePEc:cdl:econwp:qt3883h8j1
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    References listed on IDEAS

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    1. Danielle Li, 2017. "Expertise versus Bias in Evaluation: Evidence from the NIH," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 60-92, April.
    2. Cassidy R. Sugimoto & Blaise Cronin, 2013. "Citation gamesmanship: testing for evidence of ego bias in peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 851-862, June.
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    1. Ryan Liu & Steven Jecmen & Vincent Conitzer & Fei Fang & Nihar B Shah, 2024. "Testing for reviewer anchoring in peer review: A randomized controlled trial," PLOS ONE, Public Library of Science, vol. 19(11), pages 1-19, November.

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