Harnessing WordNet senses for supervised sentiment classification

EMNLP, pp. 1081-1091, 2011.

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Abstract:

Traditional approaches to sentiment classification rely on lexical features, syntax-based features or a combination of the two. We propose semantic features using word senses for a supervised document-level sentiment classifier. To highlight the benefit of sense-based features, we compare word-based representation of documents with a sens...More

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