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dc.contributorRomero Merino, Enrique
dc.contributorPadró, Lluís
dc.contributorGallego Dobón, Aina
dc.contributor.authorBeltrán Jorba, Javier
dc.description.abstractThis work uses Twitter data from Spanish politicians to discover differences in how men and women speak in politics, as well as differences in how men and women politicians are addressed by others. A tool for automatic detection of hostile answers to politicians is also developed from a labeled set.
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshNatural language processing (Computer science)
dc.subject.lcshArtificial intelligence
dc.subject.lcshSocial networks
dc.subject.othernatural language processing
dc.subject.othersocial data
dc.subject.othersocial science
dc.subject.othermachine learning
dc.subject.otherverbal abuse
dc.subject.otherartificial intelligence
dc.titleAnalyzing Twitter data to discover gender biases in Spanish politics
dc.title.alternativeAnalysis of sexist language in Twitter
dc.typeMaster thesis
dc.subject.lemacTractament del llenguatge natural (Informàtica)
dc.subject.lemacIntel·ligència artificial
dc.subject.lemacXarxes socials
dc.rights.accessOpen Access
dc.audience.mediatorFacultat d'Informàtica de Barcelona
dc.contributor.covenanteeUniversitat de Barcelona. Facultat de Matemàtiques i Informàtica
dc.contributor.covenanteeUniversitat Rovira i Virgili. Escola Tècnica Superior d'Enginyeria

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