  In this paper, we analyze web-downloaded data on people sharing their music
library. By attributing to each music group usual music genres (Rock, Pop...),
and analysing correlations between music groups of different genres with
percolation-idea based methods, we probe the reality of these subdivisions and
construct a music genre cartography, with a tree representation. We also show
the diversity of music genres with Shannon entropy arguments, and discuss an
alternative objective way to classify music, that is based on the complex
structure of the groups audience. Finally, a link is drawn with the theory of
hidden variables in complex networks.
