Cluster Analysis on musical data from Last.Fm

On the left a graph of 388 users of is shown. The users are selected by recursively descending the list of neighbours that computes for each user. A measure of similarity is computed by for each neighbour. The algorithm of this similarity computation is unfortunately not disclosed.
The graph shows a traversal of 2 levels deep, starting from myself as root, but selecting only neighbours with a similarity higher than 50 (similarities range from 0..100). The result is a list of 388 users. The outgoing edges from each user in the graph point to the 3 most similar neighbours.
By computing the optimal modularity the graph has been split into 6 clusters. For each cluster the table below shows the 10 most played artists/composers.

C-52 C-77 C-58 C-61 C-62 C-73
0.067Esbjörn Svensson Trio 0.075Johann Sebastian Bach 0.199Sufjan Stevens 0.172Fabrizio De André 0.084Muse 0.127The Beatles
0.037Keith Jarrett 0.036Wolfgang Amadeus Mozart 0.024Regina Spektor 0.032Pink Floyd 0.079Placebo 0.103Jamiroquai
0.022Bill Evans 0.034Ludwig van Beethoven 0.022The Beatles 0.016Franco Battiato 0.037Mew 0.031Queen
0.020Miles Davis 0.033Frédéric Chopin 0.017Rufus Wainwright 0.016Radiohead 0.024Scandinavian Music Group 0.014Yavuz Çetin
0.019Chick Corea 0.026Franz Schubert 0.013Thomas Newman 0.015Francesco Guccini 0.023Radiohead 0.014Aziza Mustafa Zadeh
0.017Pat Metheny 0.021Johannes Brahms 0.012Death Cab for Cutie 0.012The Beatles 0.023Lapko 0.010Radiohead
0.017Brad Mehldau 0.017Georg Friedrich Händel 0.012Elliott Smith 0.012Vinicio Capossela 0.023Zen Café 0.009Pink Floyd
0.016Herbie Hancock 0.015Pyotr Ilyich Tchaikovsky 0.011The Shins 0.011Modena City Ramblers 0.020The Ark 0.009Dream Theater
0.015Thelonious Monk 0.015Antonio Vivaldi 0.010Belle and Sebastian 0.011Rino Gaetano 0.020The Killers 0.008Red Hot Chili Peppers
0.012John Coltrane 0.014Felix Mendelssohn 0.010Feist 0.010Elio e le Storie Tese 0.018Coldplay 0.008Led Zeppelin