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Novel citation-based search method for scientific literature: a validation study

BACKGROUND: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation sea...

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Autores principales: Janssens, A. Cecile J. W., Gwinn, Marta, Brockman, J. Elaine, Powell, Kimberley, Goodman, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006380/
https://www.ncbi.nlm.nih.gov/pubmed/32028894
http://dx.doi.org/10.1186/s12874-020-0907-5
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author Janssens, A. Cecile J. W.
Gwinn, Marta
Brockman, J. Elaine
Powell, Kimberley
Goodman, Michael
author_facet Janssens, A. Cecile J. W.
Gwinn, Marta
Brockman, J. Elaine
Powell, Kimberley
Goodman, Michael
author_sort Janssens, A. Cecile J. W.
collection PubMed
description BACKGROUND: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. METHODS: We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles. RESULTS: A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. CONCLUSIONS: CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible.
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spelling pubmed-70063802020-02-13 Novel citation-based search method for scientific literature: a validation study Janssens, A. Cecile J. W. Gwinn, Marta Brockman, J. Elaine Powell, Kimberley Goodman, Michael BMC Med Res Methodol Research Article BACKGROUND: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. METHODS: We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles. RESULTS: A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. CONCLUSIONS: CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible. BioMed Central 2020-02-07 /pmc/articles/PMC7006380/ /pubmed/32028894 http://dx.doi.org/10.1186/s12874-020-0907-5 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Research Article
Janssens, A. Cecile J. W.
Gwinn, Marta
Brockman, J. Elaine
Powell, Kimberley
Goodman, Michael
Novel citation-based search method for scientific literature: a validation study
title Novel citation-based search method for scientific literature: a validation study
title_full Novel citation-based search method for scientific literature: a validation study
title_fullStr Novel citation-based search method for scientific literature: a validation study
title_full_unstemmed Novel citation-based search method for scientific literature: a validation study
title_short Novel citation-based search method for scientific literature: a validation study
title_sort novel citation-based search method for scientific literature: a validation study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006380/
https://www.ncbi.nlm.nih.gov/pubmed/32028894
http://dx.doi.org/10.1186/s12874-020-0907-5
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