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Microtexts are a valuable, albeit noisy, source to infer collaborative information. As music plays an important role in many human lives, microblogs on musicrelated activities are available in abundance. This paper investigates different strategies to estimate music similarity from these data sources. In particular, we first present a framework to extract co-occurrence scores between music artists from microblogs and then investigate 12 similarity estimation functions to subsequently derivedoi:10.1007/s00530-013-0321-5 fatcat:dm7hmwwg5feclhryi74i4gsdlu