Experiments on summary-based opinion classification

  • Authors:
  • Elena Lloret;Horacio Saggion;Manuel Palomar

  • Affiliations:
  • University of Alicante, Alicante, Spain;Universitat Pompeu Fabra, Barcelona, Spain;University of Alicante, Alicante, Spain

  • Venue:
  • CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
  • Year:
  • 2010

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Abstract

We investigate the effect of text summarisation in the problem of rating-inference -- the task of associating a fine-grained numerical rating to an opinionated document. We set-up a comparison framework to study the effect of different summarisation algorithms of various compression rates in this task and compare the classification accuracy of summaries and documents for associating documents to classes. We make use of SVM algorithms to associate numerical ratings to opinionated documents. The algorithms are informed by linguistic and sentiment-based features computed from full documents and summaries. Preliminary results show that some types of summaries could be as effective or better as full documents in this problem.