Sentiment classification using semantic features extracted from WordNet-based resources

Authors:
Yoan Gutiérrez;Sonia Vázquez;Andrés Montoyo
Affiliations:
University of Matanzas, Cuba;University of Alicante, Spain;University of Alicante, Spain
Venue:
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Year:
2011

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Abstract

In this paper, we concentrate on the 3 of the tracks proposed in the NTCIR 8 MOAT, concerning the classification of sentences according to their opinionatedness, relevance and polarity. We propose a method for the detection of opinions, relevance, and polarity classification, based on ISR-WN (a resource for the multidimensional analysis with Relevant Semantic Trees of sentences using different WordNet-based information sources). Based on the results obtained, we can conclude that the resource and methods we propose are appropriate for the task, reaching the level of state-of-the-art approaches.