Global music streaming data reveal diurnal and seasonal patterns of affective preference

Minsu Park (), Jennifer Thom, Sarah Mennicken, Henriette Cramer and Michael Macy ()
Additional contact information
Minsu Park: Cornell University
Jennifer Thom: Spotify USA
Sarah Mennicken: Spotify USA
Henriette Cramer: Spotify USA
Michael Macy: Cornell University

Nature Human Behaviour, 2019, vol. 3, issue 3, 230-236

Abstract: Abstract People manage emotions to cope with life’s demands1,2. Previous research has identified affective patterns using self-reports3 and text analysis4,5, but these measures track the expression of affect, not affective preference for external stimuli such as music, which affects mood states and levels of emotional arousal1,6,7. We analysed a dataset of 765 million online music plays streamed by 1 million individuals in 51 countries to measure diurnal and seasonal patterns of affective preference. Findings reveal similar diurnal patterns across cultures and demographic groups. Individuals listen to more relaxing music late at night and more energetic music during normal business hours, including mid-afternoon when affective expression is lowest. However, there were differences in baselines: younger people listen to more intense music; compared with other regions, music played in Latin America is more arousing, while music in Asia is more relaxing; and compared with other chronotypes, ‘night owls’ (people who are habitually active or wakeful at night) listen to less-intense music. Seasonal patterns vary with distance from the equator and between Northern and Southern hemispheres and are more strongly correlated with absolute day length than with changes in day length. Taken together with previous findings on affective expression in text4, these results suggest that musical choice both shapes and reflects mood.

Date: 2019
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DOI: 10.1038/s41562-018-0508-z

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