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Large-scale language analysis of peer review reports

Peer review is often criticized for being flawed, subjective and biased, but research into peer review has been hindered by a lack of access to peer review reports. Here we report the results of a study in which text-analysis software was used to determine the linguistic characteristics of 472,449 p...

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Detalles Bibliográficos
Autores principales: Buljan, Ivan, Garcia-Costa, Daniel, Grimaldo, Francisco, Squazzoni, Flaminio, Marušić, Ana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390598/
https://www.ncbi.nlm.nih.gov/pubmed/32678065
http://dx.doi.org/10.7554/eLife.53249
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author Buljan, Ivan
Garcia-Costa, Daniel
Grimaldo, Francisco
Squazzoni, Flaminio
Marušić, Ana
author_facet Buljan, Ivan
Garcia-Costa, Daniel
Grimaldo, Francisco
Squazzoni, Flaminio
Marušić, Ana
author_sort Buljan, Ivan
collection PubMed
description Peer review is often criticized for being flawed, subjective and biased, but research into peer review has been hindered by a lack of access to peer review reports. Here we report the results of a study in which text-analysis software was used to determine the linguistic characteristics of 472,449 peer review reports. A range of characteristics (including analytical tone, authenticity, clout, three measures of sentiment, and morality) were studied as a function of reviewer recommendation, area of research, type of peer review and reviewer gender. We found that reviewer recommendation had the biggest impact on the linguistic characteristics of reports, and that area of research, type of peer review and reviewer gender had little or no impact. The lack of influence of research area, type of review or reviewer gender on the linguistic characteristics is a sign of the robustness of peer review.
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spelling pubmed-73905982020-07-31 Large-scale language analysis of peer review reports Buljan, Ivan Garcia-Costa, Daniel Grimaldo, Francisco Squazzoni, Flaminio Marušić, Ana eLife Feature Article Peer review is often criticized for being flawed, subjective and biased, but research into peer review has been hindered by a lack of access to peer review reports. Here we report the results of a study in which text-analysis software was used to determine the linguistic characteristics of 472,449 peer review reports. A range of characteristics (including analytical tone, authenticity, clout, three measures of sentiment, and morality) were studied as a function of reviewer recommendation, area of research, type of peer review and reviewer gender. We found that reviewer recommendation had the biggest impact on the linguistic characteristics of reports, and that area of research, type of peer review and reviewer gender had little or no impact. The lack of influence of research area, type of review or reviewer gender on the linguistic characteristics is a sign of the robustness of peer review. eLife Sciences Publications, Ltd 2020-07-17 /pmc/articles/PMC7390598/ /pubmed/32678065 http://dx.doi.org/10.7554/eLife.53249 Text en © 2020, Buljan et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Feature Article
Buljan, Ivan
Garcia-Costa, Daniel
Grimaldo, Francisco
Squazzoni, Flaminio
Marušić, Ana
Large-scale language analysis of peer review reports
title Large-scale language analysis of peer review reports
title_full Large-scale language analysis of peer review reports
title_fullStr Large-scale language analysis of peer review reports
title_full_unstemmed Large-scale language analysis of peer review reports
title_short Large-scale language analysis of peer review reports
title_sort large-scale language analysis of peer review reports
topic Feature Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390598/
https://www.ncbi.nlm.nih.gov/pubmed/32678065
http://dx.doi.org/10.7554/eLife.53249
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