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.
@article{arxiv.1605.08486,
title = {Mixtape Application: Last.fm Data Characterization},
author = {Luciana Fujii Pontello and Pedro H. F. Holanda and Bruno Guilherme and Joao Paulo V. Cardoso and Olga Goussevskaia and Ana Paula Couto Silva},
journal= {arXiv preprint arXiv:1605.08486},
year = {2016}
}