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Tag2Risk Harnessing Social Music Tags for Characterizing Depression Risk

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Document pages: 14 pages

Abstract: Musical preferences have been considered a mirror of the self. In this age ofBig Data, online music streaming services allow us to capture ecologicallyvalid music listening behavior and provide a rich source of information toidentify several user-specific aspects. Studies have shown musical engagementto be an indirect representation of internal states including internalizedsymptomatology and depression. The current study aims at unearthing patternsand trends in the individuals at risk for depression as it manifests innaturally occurring music listening behavior. Mental well-being scores, musicalengagement measures, and listening histories of this http URL users (N=541) wereacquired. Social tags associated with each listener s most popular tracks wereanalyzed to unearth the mood emotions and genres associated with the users.Results revealed that social tags prevalent in the users at risk for depressionwere predominantly related to emotions depicting Sadness associated with genretags representing neo-psychedelic-, avant garde-, dream-pop. This study willopen up avenues for an MIR-based approach to characterizing and predicting riskfor depression which can be helpful in early detection and additionally providebases for designing music recommendations accordingly.

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