Supervised polarity classification of Spanish tweets based on linguistic knowledge

Authors:
David Vilares;Miguel Ángel Alonso;Carlos Gómez-Rodríguez
Affiliations:
Universidade da Coruña, A coruña, Spain;Universidade da Coruña, A Coruña, Spain;Universidade da Coruña, A Coruña, Spain
Venue:
Proceedings of the 2013 ACM symposium on Document engineering
Year:
2013

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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.