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Self-defined information indices: application to the case of university rankings

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Self-defined information indices: application to the case of university rankings

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dc.contributor.author Ferrer Sapena, Antonia es_ES
dc.contributor.author Erdogan, E. es_ES
dc.contributor.author Jiménez-Fernández, E. es_ES
dc.contributor.author Sánchez Pérez, Enrique Alfonso es_ES
dc.contributor.author Peset Mancebo, María Fernanda es_ES
dc.date.accessioned 2021-09-03T03:33:55Z
dc.date.available 2021-09-03T03:33:55Z
dc.date.issued 2020-06 es_ES
dc.identifier.issn 0138-9130 es_ES
dc.identifier.uri http://hdl.handle.net/10251/171320
dc.description.abstract [EN] University rankings are now relevant decision-making tools for both institutional and private purposes in the management of higher education and research. However, they are often computed only for a small set of institutions using some sophisticated parameters. In this paper we present a new and simple algorithm to calculate an approximation of these indices using some standard bibliometric variables, such as the number of citations from the scientific output of universities and the number of articles per quartile. To show our technique, some results for the ARWU index are presented. From a technical point of view, our technique, which follows a standard machine learning scheme, is based on the interpolation of two classical extrapolation formulas for Lipschitz functions defined in metric spaces-the so-called McShane and Whitney formulae-. In the model, the elements of the metric space are the universities, the distances are measured using some data that can be extracted from the Incites database, and the Lipschitz function is the ARWU index. es_ES
dc.description.sponsorship The third and fourth authors gratefully acknowledge the support of the Ministerio de Ciencia, Innovacion y Universidades (Spain), Agencia Estatal de Investigacion, and FEDER, under Grant MTM2016-77054-C2-1-P. The first author gratefully acknowledge the support of Catedra de Transparencia y Gestion de Datos, Universitat Politecnica de Valencia y Generalitat Valenciana, Spain. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Scientometrics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Reinforcement learning es_ES
dc.subject Metric space es_ES
dc.subject Lipschitz extension es_ES
dc.subject Shanghai es_ES
dc.subject ARWU es_ES
dc.subject University ranking es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.subject.classification BIBLIOTECONOMIA Y DOCUMENTACION es_ES
dc.title Self-defined information indices: application to the case of university rankings es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11192-020-03575-6 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//MTM2016-77054-C2-1-P/ES/ANALISIS NO LINEAL, INTEGRACION VECTORIAL Y APLICACIONES EN CIENCIAS DE LA INFORMACION/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicación Audiovisual, Documentación e Historia del Arte - Departament de Comunicació Audiovisual, Documentació i Història de l'Art es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation Ferrer Sapena, A.; Erdogan, E.; Jiménez-Fernández, E.; Sánchez Pérez, EA.; Peset Mancebo, MF. (2020). Self-defined information indices: application to the case of university rankings. Scientometrics. 124(3):2443-2456. https://doi.org/10.1007/s11192-020-03575-6 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s11192-020-03575-6 es_ES
dc.description.upvformatpinicio 2443 es_ES
dc.description.upvformatpfin 2456 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 124 es_ES
dc.description.issue 3 es_ES
dc.relation.pasarela S\423783 es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Cátedra de Transparencia y Gestión de datos, Universitat Politècnica de València es_ES
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