Supervised polarity classification of Spanish tweets based on linguistic knowledge
David Vilares, Miguel Á. Alonso, Carlos Gómez‐Rodríguez · 2013
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.