Social Tagging and Music Information Retrieval

Abstract

Social tags are free text labels that are applied to items such as artists, albums and songs. Captured in these tags is a great deal of information that is highly relevant to Music Information Retrieval (MIR) researchers including information about genre, mood, instrumentation, and quality. Unfortunately there is also a great deal of irrelevant information and noise in the tags. Imperfect as they may be, social tags are a source of human-generated contextual knowledge about music that may become an essential part of the solution to many MIR problems.

In this article, we describe the state of the art in commercial and research social tagging systems for music. We describe how tags are collected and used in current systems. We explore some of the issues that are encountered when using tags, and we suggest possible areas of exploration for future research.

Acknowledgements

Thanks to the many individuals that provided input and support including the management at Last.fm and Sun Microsystems Inc., Jeff Alexander, Jean-Julien Aucouturier, Thierry Bertin-Mahieux, Don Byrd, Oscar Celma, Douglas Eck, Stephen Green, David Jennings, Edith Law, Michael Mandel, Elias Pampalk and Douglas Turnbull. Thanks also to the anonymous reviewers who provided many useful comments and suggestions.

Notes

¹Audioscrobbler web services described at http://www.audio scrobbler.net/data/webservices/.