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Measuring National Happiness with Music

Author

Listed:
  • Benetos, Emmanouil

    (Queen Mary University of London and The Alan Turing Institute)

  • Ragano, Alessandro

    (University College Dublin)

  • Sgroi, Daniel

    (University of Warwick, ESRC CAGE Centre and IZA Bonn.)

  • Tuckwell, Anthony

    (University of Warwick and ESRC CAGE Centre.)

Abstract

We propose a new measure for national happiness based on the emotional content of a country’s most popular songs. Using machine learning to detect the valence of the UK’s chart-topping song of each year since the 1970s, we find that it reliably predicts the leading survey-based measure of life satisfaction. Moreover, we find that music valence is better able to predict life satisfaction than a recently-proposed measure of happiness based on the valence of words in books (Hills et al., 2019). Our results have implications for the role of music in society, and at the same time validate a new use of music as a measure of public sentiment.

Suggested Citation

  • Benetos, Emmanouil & Ragano, Alessandro & Sgroi, Daniel & Tuckwell, Anthony, 2021. "Measuring National Happiness with Music," CAGE Online Working Paper Series 537, Competitive Advantage in the Global Economy (CAGE).
    • Handle: RePEc:cge:wacage:537
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    File URL: https://warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/wp537.2021.pdf
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    References listed on IDEAS

    as
    1. Ed Diener & Shigehiro Oishi & Louis Tay, 2018. "Advances in subjective well-being research," Nature Human Behaviour, Nature, vol. 2(4), pages 253-260, April.
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    Cited by:

    1. Alexandre Hyafil & Nicolas Baumard, 2022. "Evoked and transmitted culture models: Using bayesian methods to infer the evolution of cultural traits in history," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-21, April.

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    More about this item

    Keywords

    subjective wellbeing; life satisfaction; national happiness; music information retrieval; machine learning. JEL Classification: N30; Z11; Z13;
    All these keywords.

    JEL classification:

    • N3 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy

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