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Mining microblogs to infer music artist similarity and cultural listening patterns
2012
Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion
This paper aims at leveraging microblogs to address two challenges in music information retrieval (MIR), similarity estimation between music artists and inferring typical listening patterns at different granularity levels (city, country, global). From two collections of several million microblogs, which we gathered over ten months, music-related information is extracted and statistically analyzed. We propose and evaluate four co-occurrence-based methods to compute artist similarity scores.
doi:10.1145/2187980.2188218
dblp:conf/www/SchedlH12
fatcat:5cyg6k6lt5eq3fs6lunu5tykea