Evidence map›Paper›PMID 37418377›Full record

Observational studyPloS one2023

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

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

Abstract readObservational Study
In one paragraph

Observational study in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ivan StelmakhNew Economic School, Moscow, Russia.ORCID 0000-0002-9237-7379
Charvi RastogiSchool of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0003-0820-4115
Ryan LiuSchool of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.ORCID 0009-0003-8755-649X
Shuchi ChawlaDepartment of Computer Science, University of Texas at Austin, Austin, Texas, United States of America.
Federico EcheniqueDivision of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California, United States of America.
Nihar B ShahSchool of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Peer ReviewResearch PersonnelBiasHumansMachine LearningPeer Review, ResearchProspective Studies

Identifiers

PMID37418377
PMCPMC10328240

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.