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Estimating the prevalence of text overlap in biomedical conference abstracts

BACKGROUND: Scientists communicate progress and exchange information via publication and presentation at scientific meetings. We previously showed that text similarity analysis applied to Medline can identify and quantify plagiarism and duplicate publications in peer-reviewed biomedical journals. In...

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Autores principales: Kinney, Nick, Wubah, Araba, Roig, Miguel, Garner, Harold R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849107/
https://www.ncbi.nlm.nih.gov/pubmed/33517918
http://dx.doi.org/10.1186/s41073-020-00106-y
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author Kinney, Nick
Wubah, Araba
Roig, Miguel
Garner, Harold R.
author_facet Kinney, Nick
Wubah, Araba
Roig, Miguel
Garner, Harold R.
author_sort Kinney, Nick
collection PubMed
description BACKGROUND: Scientists communicate progress and exchange information via publication and presentation at scientific meetings. We previously showed that text similarity analysis applied to Medline can identify and quantify plagiarism and duplicate publications in peer-reviewed biomedical journals. In the present study, we applied the same analysis to a large sample of conference abstracts. METHODS: We downloaded 144,149 abstracts from 207 national and international meetings of 63 biomedical conferences. Pairwise comparisons were made using eTBLAST: a text similarity engine. A domain expert then reviewed random samples of highly similar abstracts (1500 total) to estimate the extent of text overlap and possible plagiarism. RESULTS: Our main findings indicate that the vast majority of textual overlap occurred within the same meeting (2%) and between meetings of the same conference (3%), both of which were significantly higher than instances of plagiarism, which occurred in less than .5% of abstracts. CONCLUSIONS: This analysis indicates that textual overlap in abstracts of papers presented at scientific meetings is one-tenth that of peer-reviewed publications, yet the plagiarism rate is approximately the same as previously measured in peer-reviewed publications. This latter finding underscores a need for monitoring scientific meeting submissions – as is now done when submitting manuscripts to peer-reviewed journals – to improve the integrity of scientific communications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41073-020-00106-y.
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spelling pubmed-78491072021-02-03 Estimating the prevalence of text overlap in biomedical conference abstracts Kinney, Nick Wubah, Araba Roig, Miguel Garner, Harold R. Res Integr Peer Rev Research BACKGROUND: Scientists communicate progress and exchange information via publication and presentation at scientific meetings. We previously showed that text similarity analysis applied to Medline can identify and quantify plagiarism and duplicate publications in peer-reviewed biomedical journals. In the present study, we applied the same analysis to a large sample of conference abstracts. METHODS: We downloaded 144,149 abstracts from 207 national and international meetings of 63 biomedical conferences. Pairwise comparisons were made using eTBLAST: a text similarity engine. A domain expert then reviewed random samples of highly similar abstracts (1500 total) to estimate the extent of text overlap and possible plagiarism. RESULTS: Our main findings indicate that the vast majority of textual overlap occurred within the same meeting (2%) and between meetings of the same conference (3%), both of which were significantly higher than instances of plagiarism, which occurred in less than .5% of abstracts. CONCLUSIONS: This analysis indicates that textual overlap in abstracts of papers presented at scientific meetings is one-tenth that of peer-reviewed publications, yet the plagiarism rate is approximately the same as previously measured in peer-reviewed publications. This latter finding underscores a need for monitoring scientific meeting submissions – as is now done when submitting manuscripts to peer-reviewed journals – to improve the integrity of scientific communications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41073-020-00106-y. BioMed Central 2021-02-01 /pmc/articles/PMC7849107/ /pubmed/33517918 http://dx.doi.org/10.1186/s41073-020-00106-y Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Kinney, Nick
Wubah, Araba
Roig, Miguel
Garner, Harold R.
Estimating the prevalence of text overlap in biomedical conference abstracts
title Estimating the prevalence of text overlap in biomedical conference abstracts
title_full Estimating the prevalence of text overlap in biomedical conference abstracts
title_fullStr Estimating the prevalence of text overlap in biomedical conference abstracts
title_full_unstemmed Estimating the prevalence of text overlap in biomedical conference abstracts
title_short Estimating the prevalence of text overlap in biomedical conference abstracts
title_sort estimating the prevalence of text overlap in biomedical conference abstracts
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849107/
https://www.ncbi.nlm.nih.gov/pubmed/33517918
http://dx.doi.org/10.1186/s41073-020-00106-y
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