This is a common Zenodo repository for both lastfm-360K and lastfm-1K datasets. See below the details of both datasets, including license, acknowledgements, contact, and instructions to cite. LASTFM-360K (version 1.2, March 2010). What is this? This dataset contains <user, artist, plays> tuples (for ~360,000 users) collected from Last.fm API, using the user.getTopArtists() method. Files: usersha1-artmbid-artname-plays.tsv (MD5: be672526eb7c69495c27ad27803148f1) usersha1-profile.tsv (MD5: 51159d4edf6a92cb96f87768aa2be678) mbox_sha1sum.py (MD5: feb3485eace85f3ba62e324839e6ab39) Data Statistics: File usersha1-artmbid-artname-plays.tsv: Total Lines: 17,559,530 Unique Users: 359,347 Artists with MBID: 186,642 Artists without MBID: 107,373 Data Format: The data is formatted one entry per line as follows (tab separated "\t"): File usersha1-artmbid-artname-plays.tsv: user-mboxsha1 \t musicbrainz-artist-id \t artist-name \t plays File usersha1-profile.tsv: user-mboxsha1 \t gender (m|f|empty) \t age (int|empty) \t country (str|empty) \t signup (date|empty) Example: File usersha1-artmbid-artname-plays.tsv: 000063d3fe1cf2ba248b9e3c3f0334845a27a6be \t a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432 \t u2 \t 31 ... File usersha1-profile.tsv: 000063d3fe1cf2ba248b9e3c3f0334845a27a6be \t m \t 19 \t Mexico \t Apr 28, 2008 ... LASTFM-1K (version 1.0, March 2010). What is this? This dataset contains <user, timestamp, artist, song> tuples collected from Last.fm API, using the user.getRecentTracks() method. This dataset represents the whole listening habits (till May, 5th 2009) for nearly 1,000 users. Files: userid-timestamp-artid-artname-traid-traname.tsv (MD5: 64747b21563e3d2aa95751e0ddc46b68) userid-profile.tsv (MD5: c53608b6b445db201098c1489ea497df) Data Statistics: File userid-timestamp-artid-artname-traid-traname.tsv: Total Lines: 19,150,868 Unique Users: 992 Artists with MBID: 107,528 Artists without MBDID: 69,420 Data Format: The data is formatted one entry per line as follows (tab separated, "\t"): File userid-timestamp-artid-artname-traid-traname.tsv: userid \t timestamp \t musicbrainz-artist-id \t artist-name \t musicbrainz-track-id \t track-name File userid-profile.tsv: userid \t gender ('m'|'f'|empty) \t age (int|empty) \t country (str|empty) \t signup (date|empty) Example: File userid-timestamp-artid-artname-traid-traname.tsv: user_000639 \t 2009-04-08T01:57:47Z \t MBID \t The Dogs D'Amour \t MBID \t Fall in Love Again? user_000639 \t 2009-04-08T01:53:56Z \t MBID \t The Dogs D'Amour \t MBID \t Wait Until I'm Dead ... File userid-profile.tsv: user_000639 \t m \t Mexico \t Apr 27, 2005 ... LICENSE OF BOTH DATASETS. The data contained in both datasets is distributed with permission of Last.fm. The data is made available for non-commercial use. Those interested in using the data or web services in a commercial context should contact: partners [at] last [dot] fm For more information see Last.fm terms of service ACKNOWLEDGEMENTS. Thanks to Last.fm for providing the access to this data via their web services. Special thanks to Norman Casagrande. REFERENCES. When using this dataset you must reference the Last.fm webpage. Optionally (not mandatory at all!), you can cite Chapter 3 of this book: @book{Celma:Springer2010, author = {Celma, O.}, title = {{Music Recommendation and Discovery in the Long Tail}}, publisher = {Springer}, year = {2010} } CONTACT: This data was collected by Òscar Celma @ MTG/UPF