Improving Spanish Polarity Classification Combining Different Linguistic Resources

  • Eugenio Martínez-Cámara
  • Fermín L. Cruz
  • M. Dolores Molina-González
  • M. Teresa Martín-Valdivia
  • F. Javier Ortega
  • L. Alfonso Ureña-López
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9103)

Abstract

Sentiment analysis is a challenging task which is attracting the attention of researchers. However, most of work is only focused on English documents, perhaps due to the lack of linguistic resources for other languages. In this paper, we present several Spanish opinion mining resources in order to develop a polarity classification system. In addition, we propose the combination of different features extracted from each resource in order to train a classifier over two different opinion corpora. We prove that the integration of knowledge from several resources can improve the final Spanish polarity classification system. The good results encourage us to continue developing sentiment resources for Spanish, and studying the combination of features extracted from different resources.

Keywords

Sentiment analysis Polarity classification Lexicon-based approach Sentiment feature generation 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Eugenio Martínez-Cámara
    • 1
  • Fermín L. Cruz
    • 2
  • M. Dolores Molina-González
    • 1
  • M. Teresa Martín-Valdivia
    • 1
  • F. Javier Ortega
    • 2
  • L. Alfonso Ureña-López
    • 1
  1. 1.SINAI Research GroupUniversity of JaénJaénSpain
  2. 2.Department of Languages and Computer SystemsUniversity of SevilleSevillaSpain

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