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Citation Metrics: A Primer on How (Not) to Normalize
Citation metrics are increasingly used to appraise published research. One challenge is whether and how to normalize these metrics to account for differences across scientific fields, age (year of publication), type of document, database coverage, and other factors. We discuss the pros and cons for...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012555/ https://www.ncbi.nlm.nih.gov/pubmed/27599158 http://dx.doi.org/10.1371/journal.pbio.1002542 |
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author | Ioannidis, John P. A. Boyack, Kevin Wouters, Paul F. |
author_facet | Ioannidis, John P. A. Boyack, Kevin Wouters, Paul F. |
author_sort | Ioannidis, John P. A. |
collection | PubMed |
description | Citation metrics are increasingly used to appraise published research. One challenge is whether and how to normalize these metrics to account for differences across scientific fields, age (year of publication), type of document, database coverage, and other factors. We discuss the pros and cons for normalizations using different approaches. Additional challenges emerge when citation metrics need to be combined across multiple papers to appraise the corpus of scientists, institutions, journals, or countries, as well as when trying to attribute credit in multiauthored papers. Different citation metrics may offer complementary insights, but one should carefully consider the assumptions that underlie their calculation. |
format | Online Article Text |
id | pubmed-5012555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50125552016-09-27 Citation Metrics: A Primer on How (Not) to Normalize Ioannidis, John P. A. Boyack, Kevin Wouters, Paul F. PLoS Biol Perspective Citation metrics are increasingly used to appraise published research. One challenge is whether and how to normalize these metrics to account for differences across scientific fields, age (year of publication), type of document, database coverage, and other factors. We discuss the pros and cons for normalizations using different approaches. Additional challenges emerge when citation metrics need to be combined across multiple papers to appraise the corpus of scientists, institutions, journals, or countries, as well as when trying to attribute credit in multiauthored papers. Different citation metrics may offer complementary insights, but one should carefully consider the assumptions that underlie their calculation. Public Library of Science 2016-09-06 /pmc/articles/PMC5012555/ /pubmed/27599158 http://dx.doi.org/10.1371/journal.pbio.1002542 Text en © 2016 Ioannidis et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Perspective Ioannidis, John P. A. Boyack, Kevin Wouters, Paul F. Citation Metrics: A Primer on How (Not) to Normalize |
title | Citation Metrics: A Primer on How (Not) to Normalize |
title_full | Citation Metrics: A Primer on How (Not) to Normalize |
title_fullStr | Citation Metrics: A Primer on How (Not) to Normalize |
title_full_unstemmed | Citation Metrics: A Primer on How (Not) to Normalize |
title_short | Citation Metrics: A Primer on How (Not) to Normalize |
title_sort | citation metrics: a primer on how (not) to normalize |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012555/ https://www.ncbi.nlm.nih.gov/pubmed/27599158 http://dx.doi.org/10.1371/journal.pbio.1002542 |
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