Unsupervised Word Polarity Tagging by Exploiting Continuous Word Representations

• Autores: Aitor García Pablos, Montse Cuadros, Germán Rigau Claramunt
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 55, 2015, págs. 127-134
• Idioma: inglés
• Títulos paralelos:
  • Etiquetado no supervisado de la polaridad de las palabras utilizando representaciones continuas de palabras
• Enlaces
  • Texto completo
• Dialnet Métricas: 2 Citas
• Resumen
  • español

    El análisis de sentimiento es un campo del procesamiento del lenguaje natural que se encarga de determinar la polaridad (positiva, negativa, neutral) en los textos en los que se vierten opiniones. Un recurso habitual en los sistemas de análisis de sentimiento son los lexicones de polaridad. Un lexicón de polaridad es un diccionario que asigna un valor predeterminado de polaridad a una palabra. En este trabajo exploramos la posibilidad de generar de manera automática lexicones de polaridad adaptados a un dominio usando representaciones continuas de palabras, en concreto la popular herramienta Word2Vec. Primero mostramos una evaluación cualitativa de la polaridad sobre un pequeño conjunto de palabras, y después mostramos los resultados de nuestra competición en la tarea 12 del SemEval-2015 usando este método.

  • English

    Sentiment analysis is the area of Natural Language Processing that aims to determine the polarity (positive, negative, neutral) contained in an opinionated text. A usual resource employed in many of these approaches are the so-called polarity lexicons. A polarity lexicon acts as a dictionary that assigns a sentiment polarity value to words. In this work we explore the possibility of automatically generating domain adapted polarity lexicons employing continuous word representations, in particular the popular tool Word2Vec. First we show a qualitative evaluation of a small set of words, and then we show our results in the SemEval-2015 task 12 using the presented method.

• Referencias bibliográficas
  • Agerri, R. and A. Garcia. 2009. QWordNet: Extracting Polarity from WordNet Senses. Seventh Conference on International Language Resources...
  • Baccianella, S., A. Esuli, and F. Sebastiani. 2010. SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining....
  • Bengio, Y., R. Ducharme, P. Vincent, and C. Janvin. 2003. A Neural Probabilistic Language Model. The Journal of Machine Learning Research,...
  • Brody, S. and N Elhadad. 2010. An unsupervised aspect-sentiment model for online reviews. The 2010 Annual Conference of the North American...
  • Choi, Y. and C. Cardie. 2009. Adapting a polarity lexicon using integer linear programming for domain-specific sentiment classification. In...
  • Cruz, F. L, J. A. Troyano, F. Enriquez, and J. Ortega. 2008. Clasificación de documentos basada en la opinión: experimentos con un corpus...
  • Dumais, S, G Furnas, T Landauer, S Deerwester, S Deerwester, et al. 1995. Latent semantic indexing. In Proceedings of the Text Retrieval Conference.
  • Dumais, S. T. 2004. Latent semantic analysis. Annual review of information science and technology, 38(1):188–230.
  • Esuli, A., F. Sebastiani, and V. G. Moruzzi. 2006. SentiWord-Net : A Publicly Available Lexical Resource for Opinion Mining. Proceedings of...
  • Fellbaum, C. 1998. WordNet. Wiley Online Library.
  • Guerini, M., L. Gatti, and M. Turchi. 2013. Sentiment Analysis : How to Derive Prior Polarities from SentiWordNet. Emnlp, pages 1259–1269.
  • Hatzivassiloglou, V., V. Hatzivassiloglou, K.R. McKeown, and K.R. McKeown. 1997. Predicting the semantic orientation of adjectives. Proceedings...
  • Huang, E. H, R. Socher, C. D. Manning, and A. Ng. 2012. Improving word representations via global context and multiple word prototypes. In...
  • Kim, J. 2013. Deriving adjectival scales from continuous space word representations. Emnlp, (October):1625–1630.
  • Liu, B. 2012. Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, 5(1):1– 167.
  • Maks, I., R. Izquierdo, F. Frontini, R. Agerri, A. Azpeitia, and P. Vossen. 2014. Generating Polarity Lexicons with WordNet propagation in...
  • Mikolov, T., K. Chen, G. Corrado, and J. Dean. 2013a. Efficient Estimation of Word Representations in Vector Space. arXiv preprint arXiv:1301.3781,...
  • Mikolov, T., I. Sutskever, K. Chen, G. Corrado, and J. Dean. 2013b. Distributed Representations of Words and Phrases and their Compositionality. arXiv...
  • Mikolov, T., W. Yih, and G. Zweig. 2013. Linguistic regularities in continuous space word representations. Proceedings of NAACL-HLT, pages...
  • Pang, B. and L. Lee. 2008. Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2):1–135.
  • Pavlopoulos, J. and I. Androutsopoulos. 2014 Aspect term extraction for sentiment analysis: New datasets, new evaluation measures and an improved...
  • Qiu, G., B. Liu, J. Bu, and C. Chen. 2011. Opinion word expansion and target extraction through double propa-gation. Computational linguistics,...
  • Ramos, C. and N. C. Marques. 2005. Determining the Polarity of Words through a Common Online Dictionary.
  • Socher, R, A. Perelygin, J.Y. Wu, and J. Chuang. 2013. Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. newdesign.aclweb.org.
  • Taboada, M., J. Brooke, M. Tofiloski, K. Voll, and M. Stede. 2011. Lexicon-Based Methods for Sentiment Analysis. Computational Linguistics,...
  • Tang, D., F. Wei, N. Yang, M. Zhou, T. Liu, and B. Qin. 2014. Learning sentimentspecific word embedding for twitter sentiment classification....
  • Turian, J., L. Ratinov, and Y. Bengio. 2010. Word Representations: A Simple and General Method for Semi-supervised Learning. Proceedings of...
  • Turney, P. D. 2002. Thumbs Up or Thumbs Down? Semantic Orienta-tion Applied to Unsupervised Classifica-tion of Reviews. Computational Linguis-tics, (July):8.
  • Vicente, S., R. Agerri, and G. Rigau. 2014. Simple, Robust and (almost) Unsupervised Generation of Polarity Lexicons for Multiple Languages. Eacl2014.
  • Zhang, L. and B. Liu. 2014. Aspect and entity extraction for opinion mining. In Data mining and knowledge discovery for big data. Springer,...