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Credit where credit’s due: accounting for co-authorship in citation counts

I propose a new method (Pareto weights) to objectively attribute citations to co-authors. Previous methods either profess ignorance about the seniority of co-authors (egalitarian weights) or are based in an ad hoc way on the order of authors (rank weights). Pareto weights are based on the respective...

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Detalles Bibliográficos
Autor principal: Tol, Richard S. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171670/
https://www.ncbi.nlm.nih.gov/pubmed/21957320
http://dx.doi.org/10.1007/s11192-011-0451-5
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author Tol, Richard S. J.
author_facet Tol, Richard S. J.
author_sort Tol, Richard S. J.
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description I propose a new method (Pareto weights) to objectively attribute citations to co-authors. Previous methods either profess ignorance about the seniority of co-authors (egalitarian weights) or are based in an ad hoc way on the order of authors (rank weights). Pareto weights are based on the respective citation records of the co-authors. Pareto weights are proportional to the probability of observing the number of citations obtained. Assuming a Pareto distribution, such weights can be computed with a simple, closed-form equation but require a few iterations and data on a scholar, her co-authors, and her co-authors’ co-authors. The use of Pareto weights is illustrated with a group of prominent economists. In this case, Pareto weights are very different from rank weights. Pareto weights are more similar to egalitarian weights but can deviate up to a quarter in either direction (for reasons that are intuitive).
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spelling pubmed-31716702011-09-26 Credit where credit’s due: accounting for co-authorship in citation counts Tol, Richard S. J. Scientometrics Article I propose a new method (Pareto weights) to objectively attribute citations to co-authors. Previous methods either profess ignorance about the seniority of co-authors (egalitarian weights) or are based in an ad hoc way on the order of authors (rank weights). Pareto weights are based on the respective citation records of the co-authors. Pareto weights are proportional to the probability of observing the number of citations obtained. Assuming a Pareto distribution, such weights can be computed with a simple, closed-form equation but require a few iterations and data on a scholar, her co-authors, and her co-authors’ co-authors. The use of Pareto weights is illustrated with a group of prominent economists. In this case, Pareto weights are very different from rank weights. Pareto weights are more similar to egalitarian weights but can deviate up to a quarter in either direction (for reasons that are intuitive). Springer Netherlands 2011-07-16 2011 /pmc/articles/PMC3171670/ /pubmed/21957320 http://dx.doi.org/10.1007/s11192-011-0451-5 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article
Tol, Richard S. J.
Credit where credit’s due: accounting for co-authorship in citation counts
title Credit where credit’s due: accounting for co-authorship in citation counts
title_full Credit where credit’s due: accounting for co-authorship in citation counts
title_fullStr Credit where credit’s due: accounting for co-authorship in citation counts
title_full_unstemmed Credit where credit’s due: accounting for co-authorship in citation counts
title_short Credit where credit’s due: accounting for co-authorship in citation counts
title_sort credit where credit’s due: accounting for co-authorship in citation counts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171670/
https://www.ncbi.nlm.nih.gov/pubmed/21957320
http://dx.doi.org/10.1007/s11192-011-0451-5
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