Music is an integral part of daily human life, and certain types of music are often associated with certain contexts, such as specific music for sleeping or for studying. The mood-arousal hypothesis suggests that music used for studying should be uplifting to boost arousal and increase cognitive performance while previous studies suggest that music used as a sleep aid should be calm, gentle and slow to decrease arousal. In this study, we created the Study music dataset by collecting tracks from Spotify playlists with the words 'study' or 'studying' in the title or description. In comparison with a pre-existing dataset, the Sleep music dataset, we show that the music's audio features, as defined by Spotify, are highly similar. Additionally, they share most of the same genres and have similar subgroups after a k-means clustering analysis. We suggest that both sleep music and study music aim to create a pleasant but not too disturbing auditory environment, which enables one to focus on studying and to lower arousal for sleeping. Using large Spotify-based datasets, we were able to uncover similarities between music used in two different contexts one would expect to be different.
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| http://dx.doi.org/10.1038/s41598-023-31692-8 | DOI Listing |
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