# Netzschleuder network catalogue, repository and centrifuge

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You may also take a look at the source code.
The network in this dataset can be loaded directly from graph-tool with:
import graph_tool.all as gt
g = gt.collection.ns["discogs_genre"]

# discogs_genre — Discogs artist affiliations

Description

Two bipartite networks of the affiliations between musical artists and either musical genres or musical "styles," as given in the discogs.com database. An edge indicates that a given artist was involved in a production of a particular genre or style. The date of this snapshot is uncertain.1

1. Description obtained from the ICON project.

Tags
Informational Relatedness Unweighted
Citation
Upstream URL OK
http://konect.cc/networks/discogs_genre
Networks
Tip: hover your mouse over a table header to obtain a legend.
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
discogs_genre 1,754,838 19,033,891 21.69 6249.78 771.62 5.12 -0.57 0.00 4 1.00 Undirected Bipartite meta 36.8 MiB 72.8 MiB 72.0 MiB 46.0 MiB
Ridiculograms