A collaborative system for sentiment analysis

  • Authors:

  • Vassiliki Rentoumi;Stefanos Petrakis;Vangelis Karkaletsis;Manfred Klenner;George A. Vouros

  • Affiliations:

  • Inst of Informatics and Telecommunications, NCSR “Demokritos”, Greece;Institute of Computational Linguistics, University of Zurich, Switzerland;Inst of Informatics and Telecommunications, NCSR “Demokritos”, Greece;Institute of Computational Linguistics, University of Zurich, Switzerland;Artificial Intelligence Laboratory, University of the Aegean, Samos, Greece

  • Venue:
  • SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
  • Year:
  • 2010

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Abstract

In the past we have witnessed our machine learning method for sentiment analysis coping well with figurative language, but determining with uncertainty the polarity of mildly figurative cases We have shown that for these uncertain cases, a rule-based system should be consulted We evaluate this collaborative approach on the ”Rotten Tomatoes” movie reviews dataset and compare it with other state-of-the-art methods, providing further evidence in favor of this approach.