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.