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dc.contributorArratia Quesada, Argimiro
dc.contributor.authorMarías Pérez, Rubén
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.description.abstractWith the recent availability and growing popularity of social media resources such as online news sites, opportunities arise as people use information processing techniques to capture the impact such news have. This thesis explores topic modelling to do sentiment analysis of news articles on topics.
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshCapital market
dc.subject.otheranàlisi de sentiment
dc.subject.otherLatent Dirichlet Allocation (LDA)
dc.subject.othermercats financers
dc.subject.otherdistribució de Dirichlet
dc.subject.otherdistribució Beta
dc.subject.othersentiment analysis
dc.subject.otherfinancial markets
dc.subject.otherDirichlet distribution
dc.subject.otherBeta distribution
dc.subject.othermodel temàtic
dc.subject.othergibbs sampling
dc.subject.otherS&P 500
dc.subject.othertopic modelling
dc.titleRefining financial sentiment analysis with topic modelling
dc.typeMaster thesis
dc.subject.lemacMercats financers
dc.rights.accessRestricted access - confidentiality agreement
dc.audience.mediatorFacultat d'Informàtica de Barcelona

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