Netzschleuder
network catalogue, repository and centrifuge
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You may also take a look at the source code.
The networks in this dataset can be loaded directly from graph-tool with:(and likewise for the other networks available.)import graph_tool.all as gt g = gt.collection.ns["lastfm/band"]
lastfm — last.fm listening habits (2007)
- Description
Two bipartite networks from the music website last.fm, giving the user-song and user-band interactions. Nodes are users and songs/bands, and an edge (i,j) denotes that a user i listens to the song/band j.1
- Tags
- Social Online Unweighted
- Citation
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- Ò. Celma Herrada, "The Long Tail in Recommender Systems. In: Music Recommendation and Discovery." Springer, Berlin, Heidelberg (2010)., https://doi.org/10.1007/978-3-642-13287-2_4 [@sci-hub]
- Upstream URL OK
- http://konect.cc/networks/lastfm_band
- Networks
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Tip: click on the table header to sort the list. Hover your mouse over it 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 band 175,069 19,150,868 218.78 2524.08 359.89 12.99 -0.27 0.00 6 1.00 Undirected Bipartite weight time 76.7 MiB 108.0 MiB 106.0 MiB 95.3 MiB song 1,085,612 19,150,868 35.28 915.72 589.26 11.34 -0.44 0.00 6 1.00 Undirected Bipartite weight time 101.8 MiB 146.0 MiB 144.4 MiB 135.4 MiB - Ridiculograms
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band song