We describe two methods to perform sentiment analysis both on long and short texts written in Spanish language. We first present an unsupervised method based on dependency parsing which calculates the semantic orientation (SO) of the sentences in order to classify the polarity. We then propose a hybrid approach which uses the computed SO and lexico-syntactic knowledge as features for a supervised classifier. Experimental results show the utility of employing syntactic information to classify the polarity in both types of texts and the importance of defining mechanisms to adapt the system for a specific domain and social medium.
Author and article information
Departamento de Computación, Universidade da Coruña