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An EigenFactor-weighted power mean generalization of the Euclidean Index
This paper proposes a weighted generalization of the recently developed Euclidean Index. The weighting mechanism is designed to reflect the reputation of the journal within which an article appears. The weights are constructed using the Eigenfactor Article Influence percentiles scores. The rationale...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386344/ https://www.ncbi.nlm.nih.gov/pubmed/30794681 http://dx.doi.org/10.1371/journal.pone.0212760 |
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author | Haley, M. Ryan |
author_facet | Haley, M. Ryan |
author_sort | Haley, M. Ryan |
collection | PubMed |
description | This paper proposes a weighted generalization of the recently developed Euclidean Index. The weighting mechanism is designed to reflect the reputation of the journal within which an article appears. The weights are constructed using the Eigenfactor Article Influence percentiles scores. The rationale for assigning weights is that citations in more prestigious journals should be adjusted to logically reflect higher costs of production and higher vetting standards, and to partially counter several pragmatic issues surrounding truncated citation counts. Simulated and empirical demonstrations of the proposed approaches are included, which emphasize the flexibility and efficacy of the proposed generalization. |
format | Online Article Text |
id | pubmed-6386344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63863442019-03-09 An EigenFactor-weighted power mean generalization of the Euclidean Index Haley, M. Ryan PLoS One Research Article This paper proposes a weighted generalization of the recently developed Euclidean Index. The weighting mechanism is designed to reflect the reputation of the journal within which an article appears. The weights are constructed using the Eigenfactor Article Influence percentiles scores. The rationale for assigning weights is that citations in more prestigious journals should be adjusted to logically reflect higher costs of production and higher vetting standards, and to partially counter several pragmatic issues surrounding truncated citation counts. Simulated and empirical demonstrations of the proposed approaches are included, which emphasize the flexibility and efficacy of the proposed generalization. Public Library of Science 2019-02-22 /pmc/articles/PMC6386344/ /pubmed/30794681 http://dx.doi.org/10.1371/journal.pone.0212760 Text en © 2019 M. Ryan Haley 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 | Research Article Haley, M. Ryan An EigenFactor-weighted power mean generalization of the Euclidean Index |
title | An EigenFactor-weighted power mean generalization of the Euclidean Index |
title_full | An EigenFactor-weighted power mean generalization of the Euclidean Index |
title_fullStr | An EigenFactor-weighted power mean generalization of the Euclidean Index |
title_full_unstemmed | An EigenFactor-weighted power mean generalization of the Euclidean Index |
title_short | An EigenFactor-weighted power mean generalization of the Euclidean Index |
title_sort | eigenfactor-weighted power mean generalization of the euclidean index |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386344/ https://www.ncbi.nlm.nih.gov/pubmed/30794681 http://dx.doi.org/10.1371/journal.pone.0212760 |
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