Music recommendation system based on user's sentiments extracted from social networks

This paper uses a sentiment intensity metric, named Sentimeter-Br2, to extract users' sentiments from different Social Networks. The framework of the recommendation system is shown in order to extract the users' phrases, which permit song recommendations based on the user preference or present sentiment intensity. Experimental subjective tests have shown that the metric produces satisfactory results.