tgbn_genre — Last.fm users and the music genres they listen to (tgbn-genre, TGB, 2005-2009)
- Description
A temporal bipartite network of 992 users of the music website Last.fm and the music genres of the songs they listened to, from February 2005 to June 2009, from the
tgbn-genredataset of the Temporal Graph Benchmark (TGB). TGB built it by matching the songs of the Last.fm listening histories of about 1,000 users (the "Last.fm 1K" data collected by Ò. Celma) with the genre tags of the songs in the Million Song Dataset. Each listen of a song gives a timestamped edge from the user to each genre of the song, weighted by the weight of the genre for the song; TGB kept only the genres with a weight of at least 10% for a song, and that occur at least a thousand times, and cleaned the genre names of typos. A listen may thus give several edges, and repeated edges.The network has the following properties:
is_genre: whether the node is a genre (otherwise a user).name: the identifier of the user (e.g.user_000871) or the name of the genre (e.g.80s).- Edge
time: the time of the listen, in Unix time. - Edge
weight: the weight of the genre for the song listened to (between 0 and 1).
- Tags
- Social Online Preferences Weighted Multigraph Timestamps Metadata
- Citation
-
- S. Huang, F. Poursafaei, J. Danovitch, M. Fey, W. Hu, E. Rossi, J. Leskovec, M. Bronstein, G. Rabusseau, R. Rabbany, "Temporal Graph Benchmark for Machine Learning on Temporal Graphs." Advances in Neural Information Processing Systems 36 (Datasets and Benchmarks Track) (2023) 10.48550/arXiv.2307.01026 Sci-Hub
- Ò. Celma, "Music Recommendation and Discovery in the Long Tail." Springer (2010) 10.1007/978-3-642-13287-2 Sci-Hub
- T. Bertin-Mahieux, D. P. W. Ellis, B. Whitman, P. Lamere, "The Million Song Dataset." Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR), 591-596 (2011) 10.7916/D8NZ8J07 Sci-Hub
- Upstream URL OK
-
https://tgb.complexdatalab.com/docs/nodeprop/
https://github.com/shenyangHuang/TGB
http://millionsongdataset.com/ - Upstream license
- MIT
- Networks
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Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties