Big Data for gender analysis

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dc.contributor.advisorEstradé Albiol, Sònia
dc.contributor.advisorViscasillas Valls, Gemma
dc.contributor.authorGuerra Rivas, Laura
dc.date.accessioned2022-09-05T14:51:26Z
dc.date.available2022-09-05T14:51:26Z
dc.date.issued2022-06
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2022, Tutores: Sònia Estradé, Gemma Viscasillasca
dc.description.abstractThe objective of this work is to use python-based big data tools to perform a gender study of doctoral theses carried out at the Faculty of Physics of the University of Barcelona. The data used for the study is a total of 561 theses that have been obtained from the Dipòsit Digital of the University of Barcelona through Web Scraping and have been analyzed using Pythonca
dc.format.extent5 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/188713
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Guerra, 2022
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física
dc.subject.classificationEstudis de gènerecat
dc.subject.classificationDades massivescat
dc.subject.classificationTesis doctoralscat
dc.subject.classificationUniversitat de Barcelona. Facultat de Física
dc.subject.classificationTreballs de fi de grau
dc.subject.otherGender studieseng
dc.subject.otherBig dataeng
dc.subject.otherDoctoral dissertationseng
dc.subject.otherUniversity of Barcelona Faculty of Physics
dc.subject.otherBachelor's theses
dc.titleBig Data for gender analysiseng
dc.typeinfo:eu-repo/semantics/bachelorThesisca

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Treballs Finals de Grau (TFG) - Física