DAEDALUS at SemEval-2014 Task 9: Comparing Approaches for Sentiment Analysis in Twitter

This paper describes our participation at SemEval2014 sentiment analysis task, in both contextual and message polarity classification. Our idea was to compare two different techniques for sentiment analysis. First, a machine learning classifier specifically built for the task using the provided training corpus. On the other hand, a lexicon-based approach using natural language processing techniques, developed for a generic sentiment analysis task with no adaptation to the provided training corpus. Results, though far from the best runs, prove that the generic model is more robust as it achieves a more balanced evaluation for message polarity along the different test sets.