  This report analyses data collected from Last.fm and used to create a
real-time recommendation system. We collected over 2M songs and 1M tags and
372K user's listening habits. We characterize users' profiles: age, playcount,
friends, gender and country. We characterized song, artist and tag popularity,
genres of songs. Additionally we evaluated the co-occurrence of songs in users'
histories, which can be used to compute similarity between songs.
