- -

Sentiment Analysis in Twitter for Spanish

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Sentiment Analysis in Twitter for Spanish

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: version_autor_NLDB.pdf
Tamaño: 268.0Kb
Formato: PDF
Descripción: Versión del Autor.
Abrir
dc.contributor.author Pla Santamaría, Ferran es_ES
dc.contributor.author Hurtado Oliver, Lluis Felip es_ES
dc.date.accessioned 2016-07-27T12:02:47Z
dc.date.available 2016-07-27T12:02:47Z
dc.date.issued 2014
dc.identifier.isbn 978-3-319-07982-0
dc.identifier.issn 0302-9743
dc.identifier.uri http://hdl.handle.net/10251/68280
dc.description The final publication is available at Springer via http://dx.doi.org/ 10.1007/978-3-319-07983-7_27 es_ES
dc.description.abstract This paper describes a SVM-approach for Sentiment Analysis (SA) in Twitter for Spanish. This task was part of the TASS2013 workshop, which is a framework for SA that is focused on the Spanish language. We describe the approach used, and we present an experimental comparison of the approaches presented by the di erent teams that took part in the competition. We also describe the improvements that were added to our system after our participation in the competition. With these improvements, we obtained an accuracy of 62.88% and 70.25% on the SA test set for 5-level and 3-level tasks respectively. To our knowledge, these results are the best results published until now for the SA tasks of the TASS2013 workshop. es_ES
dc.description.sponsorship This work has been funded by the projects, DIANA (MEC TIN2012-38603-C02-01) and Tímpano (MEC TIN2011-28169-C05-01). es_ES
dc.format.extent 6 es_ES
dc.language Inglés es_ES
dc.publisher Springer Lecture Notes in Computer Science Volume 8455 2014 es_ES
dc.relation.ispartof Natural Language Processing and Information Systems es_ES
dc.relation.ispartofseries Lecture Notes in Computer Science;8455
dc.rights Reserva de todos los derechos es_ES
dc.subject Sentiment analysis es_ES
dc.subject Twiter es_ES
dc.subject Machine learning es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Sentiment Analysis in Twitter for Spanish es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1007/978-3-319-07983-7_27
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2012-38603-C02-01/ES/DIANA-APPLICATIONS: FINDING HIDDEN KNOWLEDGE IN TEXTS: APPLICATIONS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2011-28169-C05-01/ES/TIMPANO-UPV: TECNOLOGIAS PARA LA INTERACCION CONVERSACIONAL COMPLAJE PERSONA-MAQUINA CON APRENDIZAJE DINAMICO/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Pla Santamaría, F.; Hurtado Oliver, LF. (2014). Sentiment Analysis in Twitter for Spanish. En Natural Language Processing and Information Systems. Springer Lecture Notes in Computer Science Volume 8455 2014. 208-213. https://doi.org/10.1007/978-3-319-07983-7_27 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 19th International Conference on Application of Natural Language to Information Systems (NLDB 2014) es_ES
dc.relation.conferencedate June 18-20, 2014 es_ES
dc.relation.conferenceplace Montpellier, France es_ES
dc.relation.publisherversion http://link.springer.com/chapter/10.1007/978-3-319-07983-7_27 es_ES
dc.description.upvformatpinicio 208 es_ES
dc.description.upvformatpfin 213 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 280979 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.description.references Barbosa, L., Feng, J.: Robust sentiment detection on Twitter from biased and noisy data. In: Proceedings of the 23rd International Conference on Computational Linguistics: Posters, Association for Computational Linguistics, pp. 36–44 (2010) es_ES
dc.description.references Jansen, B.J., Zhang, M., Sobel, K., Chowdury, A.: Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology 60(11), 2169–2188 (2009) es_ES
dc.description.references Liu, B., Hu, M., Cheng, J.: Opinion observer: Analyzing and comparing opinions on the web. In: Proceedings of the 14th International Conference on World Wide Web, WWW 2005, pp. 342–351. ACM, New York (2005) es_ES
dc.description.references Martínez-Cámara, E., Martín-Valdivia, M.T., Ureña-López, L.A., Montejo-Raéz, A.: Sentiment analysis in twitter. Natural Language Engineering 1(1), 1–28 (2012) es_ES
dc.description.references O’Connor, B., Krieger, M., Ahn, D.: Tweetmotif: Exploratory search and topic summarization for twitter. In: Cohen, W.W., Gosling, S. (eds.) Proceedings of the Fourth International Conference on Weblogs and Social Media, ICWSM 2010, Washington, DC, USA, May 23-26, The AAAI Press (2010) es_ES
dc.description.references Padró, L., Stanilovsky, E.: Freeling 3.0: Towards wider multilinguality. In: Proceedings of the Language Resources and Evaluation Conference (LREC 2012). ELRA, Istanbul (2012) es_ES
dc.description.references Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? sentiment classification using machine learning techniques. In: Proceedings of EMNLP, pp. 79–86 (2002) es_ES
dc.description.references Perez-Rosas, V., Banea, C., Mihalcea, R.: Learning sentiment lexicons in spanish. In: Chair, N.C.C., Choukri, K., Declerck, T., Doǧan, M.U., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S. (eds.) Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC 2012). European Language Resources Association (ELRA), Istanbul (2012) es_ES
dc.description.references Pla, F., Hurtado, L.F.: Análisis de sentimientos en twitter. In: Proceedings of the TASS workshop at SEPLN 2013, IV Congreso Español de Informática (2013) es_ES
dc.description.references Saralegi, X., San Vicente, I.: Elhuyar at tass 2013. In: Proceedings of the TASS workshop at SEPLN 2013, IV Congreso Español de Informática (2013) es_ES
dc.description.references Schölkopf, B., Smola, A.J., Williamson, R.C., Bartlett, P.L.: New support vector algorithms. Neural Comput. 12(5), 1207–1245 (2000) es_ES
dc.description.references Turney, P.D.: Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: ACL, pp. 417–424 (2002) es_ES
dc.description.references Villena-Román, J., García-Morera, J.: Workshop on sentiment analysis at sepln 2013: An over view. In: Proceedings of the TASS Workshop at SEPLN 2013, IV Congreso Español de Informática (2013) es_ES
dc.description.references Vinodhini, G., Chandrasekaran, R.: Sentiment analysis and opinion mining: A survey. International Journal 2(6) (2012) es_ES
dc.description.references Wilson, T., Hoffmann, P., Somasundaran, S., Kessler, J., Wiebe, J., Choi, Y., Cardie, C., Riloff, E., Patwardhan, S.: Opinionfinder: A system for subjectivity analysis. In: Proceedings of HLT/EMNLP on Interactive Demonstrations, Association for Computational Linguistics, pp. 34–35 (2005) es_ES
dc.description.references Wilson, T., Kozareva, Z., Nakov, P., Rosenthal, S., Stoyanov, V., Ritter, A.: Semeval-2013 task 2: Sentiment analysis in twitter. In: Proceedings of the International Workshop on Semantic Evaluation, SemEval, vol. 13 (2013) es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem