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Sentiment analysis for reviews and microtexts based on lexico-syntactic knowledge
dc.contributor.author | Vilares, David | |
dc.date.accessioned | 2024-04-10T19:22:25Z | |
dc.date.available | 2024-04-10T19:22:25Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Vilares, D. (2013). Sentiment analysis for reviews and microtexts based on lexico-syntactic knowlegde. FDIA 2013: Fifth BCS-IRSG Symposium on Future Directions in Information Access. DOI: 10.14236/ewic/FDIA2013.8 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/36136 | |
dc.description.abstract | [Abstract]: We describe two methods to perform sentiment analysis both on long and short texts written in Spanish language. We first present an unsupervised method based on dependency parsing which calculates the semantic orientation (SO) of the sentences in order to classify the polarity. We then propose a hybrid approach which uses the computed SO and lexico-syntactic knowledge as features for a supervised classifier. Experimental results show the utility of employing syntactic information to classify the polarity in both types of texts and the importance of defining mechanisms to adapt the system for a specific domain and social medium. | es_ES |
dc.description.sponsorship | Research reported in this paper has been partially funded by Ministerio de Economía y Competitividad and FEDER ( TIN2010-18552-C03-02) and by Xunta de Galicia (CN2012/008, CN2012/319). | es_ES |
dc.description.sponsorship | Xunta de Galicia; CN2012/008 | es_ES |
dc.description.sponsorship | Xunta de Galicia; CN2012/319 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | BCS-IRSG | es_ES |
dc.relation | info: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 RELACIONES | es_ES |
dc.relation.uri | https://doi.org/10.14236/ewic/FDIA2013.8 | es_ES |
dc.rights | Atribución 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Sentiment Analysis | es_ES |
dc.subject | Opinion Mining | es_ES |
dc.subject | Dependency Parsing | es_ES |
dc.subject | Machine Learning | es_ES |
dc.title | Sentiment analysis for reviews and microtexts based on lexico-syntactic knowledge | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.startPage | 38 | es_ES |
UDC.endPage | 43 | es_ES |
dc.identifier.doi | 10.14236/ewic/FDIA2013.8 | |
UDC.conferenceTitle | FDIA 2013 : 5th Symposium on Future Directions in Information Access | es_ES |