Supervised polarity classification of Spanish tweets based on linguistic knowledge

David Vilares, Miguel Ángel Alonso, Carlos Gómez-Rodríguez
2013 Proceedings of the 2013 ACM symposium on Document engineering - DocEng '13  
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 dblp:conf/doceng/VilaresAG13 fatcat:3ii4mx6n2bg4hd7javgkyld4jq