TY  - RPRT
        AU  - Benetos, Emmanouil
AU  - Ragano, Alessandro
AU  - Sgroi, Daniel
AU  - Tuckwell, Anthony
        TI  - Measuring National Life Satisfaction  with Music
        PY  - 2021/Apr/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 14258
        UR  - https://www.iza.org/publications/dp14258
        AB  - National life satisfaction is an important way to measure societal well-being and since 2011 has been used to judge the effectiveness of government policy across the world. However, there is a paucity of historical data making limiting long-run comparisons with other data. We construct a new measure based on the emotional content of music. We first trained a machine learning model using 191 different audio features embedded within music and use this model to construct a long-run Music Valence Index derived from chart-topping songs. This index correlates strongly and significantly with survey-based life satisfaction and outperforms an equivalent text-based measure. Our results have implications for the role of music in society, and validate a new use of music as a long-run measure of public sentiment.
        KW  - historical subjective wellbeing
KW  - life satisfaction
KW  - music
KW  - sound data
KW  - language
KW  - big data
        ER  -