Supervised polarity classification of Spanish tweets based on linguistic knowledge

Abstract

We describe a system that classifies the polarity of Spanish tweets. We adopt a hybrid approach, which combines machine learning and linguistic knowledge acquired by means of NLP. We use part-of-speech tags, syntactic dependencies and semantic knowledge as features for a supervised classifier. Lexical particularities of the language used in Twitter are taken into account in a pre-processing step. Experimental results improve over those of pure machine learning approaches and confirm the practical utility of the proposal.

DOI: 10.1145/2494266.2494300

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Cite this paper

@inproceedings{Vilares2013SupervisedPC, title={Supervised polarity classification of Spanish tweets based on linguistic knowledge}, author={David Vilares and Miguel A. Alonso and Carlos G{\'o}mez-Rodr{\'i}guez}, booktitle={ACM Symposium on Document Engineering}, year={2013} }