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Genre-based Analysis of Social Media Data on Music Listening Behavior: Are Fans of Classical Music Really Averse to Social Media?

, and . WISMM, page 9-13. ACM, (2014)

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Accessing Music Collections Via Representative Cluster Prototypes in a Hierarchical Organisation Scheme, , , and . Proceedings of the 9th International Conference on Music Information Retrival, Philadelphia, USA, (September 2008)Automatically Adapting the Structure of Audio Similarity Spaces, , , and . Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals, Athens, Greece, (2006)The Million Musical Tweet Dataset - What We Can Learn From Microblogs., , , and . ISMIR, page 189-194. (2013)Order, context and popularity bias in next-song recommendations., , , and . Int. J. Multim. Inf. Retr., 8 (2): 101-113 (2019)Hybrid music information retrieval., , and . Int. J. Multim. Inf. Retr., 2 (1): 1-2 (2013)An Analysis of Agreement in Classical Music Perception and its Relationship to Listener Characteristics., , , and . ISMIR, page 578-583. (2016)I-Vectors for Timbre-Based Music Similarity and Music Artist Classification., , , and . ISMIR, page 554-560. (2015)Investigating the Similarity Space of Music Artists on the Micro-Blogosphere., , and . ISMIR, page 323-328. University of Miami, (2011)On Rhythm and General Music Similarity., , , , and . ISMIR, page 525-530. International Society for Music Information Retrieval, (2009)Accessing Music Collections Via Representative Cluster Prototypes in a Hierarchical Organization Scheme., , , and . ISMIR, page 179-184. (2008)