Sentiment analysis refers to automatically extracting the sentiment present in a given natural language text. We present our participation to the SemEval2013 competition, in the sentiment analysis of Twitter and SMS messages.
Our approach for this task is the combination of two sentiment analysis subsystems which are combined together to build the final system. Both subsystems use supervised learning using features based on various polarity lexicon
