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Popular research methods in assessing the impact of macroeconomic and environmental variables on music preferences were psychological experiments and surveys with small groups or analyzing the effect of one or two variables in the whole population. Instead inspired by the article of The Economist about February being the gloomiest month in terms of music listened to, we have created a dataset with many variables. We used Spotify API to create a dataset with average valence for 26 countries for the period from January 1, 2018, to December 1, 2019. Then we applied the regression and machine learning models to them. Our study confirmed the effects of summer, December, and the number of Saturdays in a month and contradicted the February effect. The influence of GDP per capita on the valence was confirmed, while the impact of the happiness index was disproved. All models partially confirmed the influence of the music genre on the valence. Among the weather variables, two models confirmed the significance of the temperature variable. Macroeconomic variables turned out to have non-linear relationships that made interpretations difficult, while the environmental ones clearly indicated a linear relationship with valence.
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- Hanna Dudek, Deprywacja materialna polskich gospodarstw domowych w pierwszym roku pandemii COVID-19 , Metody Ilościowe w Badaniach Ekonomicznych: Tom 22 Nr 3 (2021)
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