Supervised polarity classification of Spanish tweets based on linguistic knowledge

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UDC.coleccionInvestigaciónes_ES
UDC.conferenceTitleDocEng '13: Proceedings of the 2013 ACM Symposium on Document engineeringes_ES
UDC.departamentoLetrases_ES
UDC.endPage172es_ES
UDC.grupoInvLingua e Sociedade da Información (LYS)es_ES
UDC.startPage169es_ES
UDC.volume2013es_ES
dc.contributor.authorVilares, David
dc.contributor.authorAlonso, Miguel A.
dc.contributor.authorGómez-Rodríguez, Carlos
dc.date.accessioned2024-04-05T17:06:40Z
dc.date.available2024-04-05T17:06:40Z
dc.date.issued2013
dc.descriptionThis is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2013 ACM symposium on Document engineering (DocEng '13). Association for Computing Machinery, New York, NY, USA, 169–172. https://doi.org/10.1145/2494266.2494300.es_ES
dc.description.abstract[Abstract]: We describe a system that classifies the polarity of Spanish tweets. We adopt a hybrid approach, which combines machine learning and linguistic knowledge acquired by means of NLP. We use part-of-speech tags, syntactic dependencies and semantic knowledge as features for a supervised classifier. Lexical particularities of the language used in Twitter are taken into account in a pre-processing step. Experimental results improve over those of pure machine learning approaches and confirm the practical utility of the proposal.es_ES
dc.description.sponsorshipResearch reported in this paper has been partially funded by Ministerio de Economía y Competitividad and FEDER (Grant TIN2010-18552-C03-02) and by Xunta de Galicia (Grants CN2012/008, CN2012/319).es_ES
dc.description.sponsorshipXunta de Galicia; CN2012/008es_ES
dc.description.sponsorshipXunta de Galicia; CN2012/319es_ES
dc.identifier.citationDavid Vilares, Miguel Ángel Alonso, and Carlos Gómez-Rodríguez. 2013. Supervised polarity classification of Spanish tweets based on linguistic knowledge. In Proceedings of the 2013 ACM symposium on Document engineering (DocEng '13). Association for Computing Machinery, New York, NY, USA, 169–172. https://doi.org/10.1145/2494266.2494300es_ES
dc.identifier.doi10.1145/2494266.2494300
dc.identifier.isbn978-1-4503-1789-4
dc.identifier.urihttp://hdl.handle.net/2183/36076
dc.language.isoenges_ES
dc.publisherAssociation for Computing Machineryes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN/Plan Nacional de I+D+i 2008-2011/TIN2010-18552-C03-02/ES/ANALISIS DE TEXTOS Y RECUPERACION DE INFORMACION PARA LA MINERIA DE OPINIONES: ANALISIS DE ENUNCIADOS Y EXTRACCION DE RELACIONESes_ES
dc.relation.urihttps://doi.org/10.1145/2494266.2494300es_ES
dc.rightsTodos os dereitos reservados. All rights reserved.es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectDocument analysises_ES
dc.subjectLinguistic analysises_ES
dc.subjectMachine learninges_ES
dc.subjectOpinion mininges_ES
dc.subjectSentiment analysises_ES
dc.subjectTwitteres_ES
dc.titleSupervised polarity classification of Spanish tweets based on linguistic knowledgees_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication37dabbe9-f54f-43bb-960e-0bf3ac7e54eb
relation.isAuthorOfPublication1318edb8-3967-465c-a267-146624c05837
relation.isAuthorOfPublicatione70a3969-39f6-4458-9339-3b71756fa56e
relation.isAuthorOfPublication.latestForDiscovery37dabbe9-f54f-43bb-960e-0bf3ac7e54eb

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