Evidence map›Paper›PMID 34616596›Full record

ArticlePeerJ2021

The impact of peer review on the contribution potential of scientific papers.

Akira Matsui, Emily Chen, Yunwen Wang, Emilio Ferrara

Abstract read
In one paragraph

Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

4 authors.

Akira Matsui *Department of Computer Science, University of Southern California, Los Angeles, California, United States.
Emily Chen *Department of Computer Science, University of Southern California, Los Angeles, California, United States.ORCID 0000-0003-2363-9889
Yunwen WangAnnenberg School for Communication and Journalism, University of Southern California, Los Angeles, California, United States.ORCID 0000-0002-3197-1366
Emilio FerraraDepartment of Computer Science, University of Southern California, Los Angeles, California, United States.ORCID 0000-0002-1942-2831

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The peer-reviewing process has long been regarded as an indispensable tool in ensuring the quality of a scientific publication. While previous studies have tried to understand the process as a whole, not much effort has been devoted to investigating the determinants and impacts of the content of the peer review itself. This study leverages open data from nearly 5,000 PeerJ publications that were eventually accepted. Using sentiment analysis, Latent Dirichlet Allocation (LDA) topic modeling, mixed linear regression models, and logit regression models, we examine how the peer-reviewing process influences the acceptance timeline and contribution potential of manuscripts, and what modifications were typically made to manuscripts prior to publication. In an open review paradigm, our findings indicate that peer reviewers' choice to reveal their names in lieu of remaining anonymous may be associated with more positive sentiment in their review, implying possible social pressure from name association. We also conduct a taxonomy of the manuscript modifications during a revision, studying the words added in response to peer reviewer feedback. This study provides insights into the content of peer reviews and the subsequent modifications authors make to their manuscripts.

Indexed as

Peer review systemScience of scienceScience policy

Identifiers

PMID34616596
PMCPMC8459734

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.