Myusic: a Content-based Music Recommender System based on eVSM and Social Media

This paper presents Myusic, a platform that leverages socialmedia to produce content-based music recommendations. The design ofthe platform is based on the insight that user preferences in music canbe extracted by mining Facebook profiles, thus providing a novel and ef-fective way to sift in large music databases and overcome the cold-startproblem as well. The content-based recommendation model implementedin Myusic is eVSM [4], an enhanced version of the vector space modelbased on distributional models, Random Indexing and Quantum Nega-tion. The effectiveness of the platform is evaluated through a preliminaryuser study performed on a sample of 50 persons. The results showed that74% of users actually prefer recommendations computed by social media-based profiles with respect to those computed by a simple heuristic basedon the popularity of artists, and confirmed the usefulness of performinguser studies because of the different outcomes they can provide withrespect to offline experiments.