Spanish knowledge base generation for polarity classification from masses

  • Authors:
  • Arturo Montejo-Ráez;Manuel Carlos Díaz-Galiano;José Manuel Perea-Ortega;Luis Alfonso Ureña-López

  • Affiliations:
  • University of Jaén, Jaén, Spain;University of Jaén, Jaén, Spain;University of Jaén, Jaén, Spain;University of Jaén, Jaén, Spain

  • Venue:
  • Proceedings of the 22nd international conference on World Wide Web companion
  • Year:
  • 2013

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Abstract

This work presents a novel method for the generation of a knowledge base oriented to Sentiment Analysis from the continuous stream of published micro-blogs in social media services like Twitter. The method is simple in its approach and has shown to be effective compared to other knowledge based methods for Polarity Classification. Due to independence from language, the method has been tested on different Spanish corpora, with a minimal effort in the lexical resources involved. Although for two of the three studied corpora the obtained results did not improve those officially obtained on the same corpora, it should be noted that this is an unsupervised approach and the accuracy levels achieved were close to those levels obtained with well-known supervised algorithms.