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dc.contributor.authorMartín Martín, Alberto es_ES
dc.contributor.authorOrduña-Malea, Enriquees_ES
dc.contributor.authorDelgado López-Cózar, Emilio es_ES
dc.date.accessioned2017-11-27T14:03:43Z
dc.date.available2017-11-27T14:03:43Z
dc.date.issued2017-11-27
dc.identifier.citationMartín-Martín, A.; Orduña-Malea, E.; Delgado López-Cózar, E. A novel method for depicting academic disciplines through Google Scholar Citations: The case of Bibliometrics. Scientometrics: In press (2017). [http://hdl.handle.net/10481/48304]es_ES
dc.identifier.issn0138-9130
dc.identifier.issn1588-2861
dc.identifier.urihttp://hdl.handle.net/10481/48304
dc.descriptionThis is a post-peer-review, pre-copyedit version of an article published in Scientometrics. The final authenticated version is available online at: https://doi.org/10.1007/s11192-017-2587-4en_EN
dc.description.abstractThis article describes a procedure to generate a snapshot of the structure of a specific scientific community and their outputs based on the information available in Google Scholar Citations (GSC). We call this method MADAP (Multifaceted Analysis of Disciplines through Academic Profiles). The international community of researchers working in Bibliometrics, Scientometrics, Informetrics, Webometrics, and Altmetrics was selected as a case study. The records of the top 1,000 most cited documents by these authors according to GSC were manually processed to fill any missing information and deduplicate fields like the journal titles and book publishers. The results suggest that it is feasible to use GSC and the MADAP method to produce an accurate depiction of the community of researchers working in Bibliometrics (both specialists and occasional researchers) and their publication habits (main publication venues such as journals and book publishers). Additionally, the wide document coverage of Google Scholar (specially books and book chapters) enables more comprehensive analyses of the documents published in a specific discipline than were previously possible with other citation indexes, finally shedding light on what until now had been a blind spot in most citation analyses.en_EN
dc.description.sponsorshipResearch funded by Ministerio de Educación, Cultura y Deporte (FPU2013/05863).es_ES
dc.description.sponsorshipUniversitat Politècnica de València (PAID-10-14).es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es
dc.subjectAcademic profilesen_EN
dc.subjectGoogle Scholar Citationsen_EN
dc.subjectBibliometrics en_EN
dc.subjectScientometricsen_EN
dc.subjectInformetricsen_EN
dc.subjectWebometricsen_EN
dc.subjectAltmetricsen_EN
dc.subjectAcademic search enginesen_EN
dc.subjectScientific disciplinesen_EN
dc.subjectMADAP methoden_EN
dc.titleA novel method for depicting academic disciplines through Google Scholar Citations: The case of Bibliometricsen_EN
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1007/s11192-017-2587-4


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