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Improving Attitude Words Classification for Opinion Mining using Word Embedding

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Ortega-Bueno, R.; Medina-Pagola, JE.; Muñiz-Cuza, CE.; Rosso, P. (2019). Improving Attitude Words Classification for Opinion Mining using Word Embedding. Lecture Notes in Computer Science. 11401:971-982. https://doi.org/10.1007/978-3-030-13469-3_112

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/159146

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Title: Improving Attitude Words Classification for Opinion Mining using Word Embedding
Author: Ortega-Bueno, Reynier Medina-Pagola, José E. Muñiz-Cuza, Carlos Enrique Rosso, Paolo
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] Recognizing and classifying evaluative expressions is an important issue of sentiment analysis. This paper presents a corpus-based method for classifying attitude types (Affect, Judgment and Appreciation) and attitude ...[+]
Subjects: Appraisal framework , Attitude classification , Opinion mining , Neural network word embedding
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-13469-3_112
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/978-3-030-13469-3_112
Conference name: 23rd Iberoamerican Congress on Pattern Recognition (CIARP 2018)
Conference place: Madrid, Spain
Conference date: Noviembre 19-22,2018
Project ID:
MINISTERIO DE ECONOMIA Y EMPRESA/TIN2015-71147-C2-1-P
Thanks:
The work of the fourth author was partially supported by the SomEMBED TIN2015-71147-C2-1-P research project (MINECO/FEDER).
Type: Artículo Comunicación en congreso Capítulo de libro

References

Bloom, K., Argamon, S.: Automated learning of appraisal extraction patterns. In: Gries, S.T., Wulff, S., Davies, M. (eds.) Corpus Linguistic Applications: Current Studies, New Directions, Third edn., pp. 249–260. Rodopi B.V., Amsterdam, New York (2010)

Bloom, K., Garg, N., Argamon, S.: Extracting appraisal expressions. In: Proceedings of the Annual Conference of the NAACL-HLT, pp. 308–315. ACL (2007)

Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. ACL 5, 135–146 (2017) [+]
Bloom, K., Argamon, S.: Automated learning of appraisal extraction patterns. In: Gries, S.T., Wulff, S., Davies, M. (eds.) Corpus Linguistic Applications: Current Studies, New Directions, Third edn., pp. 249–260. Rodopi B.V., Amsterdam, New York (2010)

Bloom, K., Garg, N., Argamon, S.: Extracting appraisal expressions. In: Proceedings of the Annual Conference of the NAACL-HLT, pp. 308–315. ACL (2007)

Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. ACL 5, 135–146 (2017)

Cardellino, C.: Spanish billion words corpus and embeddings (2016)

Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321–357 (2002)

Deerwester, S., Dumais, S., Furnas, G., Landauer, T., Harshman, R.: Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci. 41(6), 391–407 (1990)

Hernández, L., López-Lopez, A., Medina-Pagola, J.E.: Recognizing polarity and attitude of words in text. In: Proceedings of 14th Portuguese Conference on Artificial Intelligence, (EPIA 2009), pp. 525–536. Aveiro, Portugal (2009)

Hernández, L., López-Lopez, A., Medina-Pagola, J.E.: Classification of attitude words for opinions mining. Int. J. Comput. Linguist. Appl. 2(1–2), 267–283 (2011)

Kanerva, P., Kristofersson, J., Holst, A.: Random indexing of text samples for latent semantic analysis. In: Proceedings of the 22 Annual Conference of the Cognitive Science Society, vol. 1036, no. 2, pp. 16429–16429 (2000)

Martin, J.R., White, P.R.R.: The Language of Evaluation: The Appraisal Framework, 1st edn. Palgrave Macmillan, New York (2005)

Mikolov, T., Corrado, G., Chen, K., Dean, J.: Efficient estimation of word representations in vector space. In: International Conference on Learning Representations (ICLR 2013), pp. 1–12 (2013)

Neviarouskaya, A., Aono, M., Prendinger, H., Ishizuka, M.: Intelligent interface for textual attitude analysis. J. ACM Trans. Intell. Syst. Technol. 5(3), 1–20 (2014)

Neviarouskaya, A., Prendinger, H., Ishizuka, M.: Attitude sensing in text based on a compositional linguistic approach. Comput. Intell. 31, 1–45 (2013)

Padró, L., Stanilovsky, E.: FreeLing 3.0: towards wider multilinguality. In: Proceedings of the (LREC 2012) (2012)

Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Commun. ACM 18(11), 613–620 (1975)

Taboada, M., Grieve, J.: Analyzing appraisal automatically. In: Proceedings of AAAI Spring Symposium on Exploring Attitude and Affect in Text, pp. 158–161. American Association for Artificial Intelligence (2004)

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