Measuring national happiness with music
Measuring national happiness with music
537/2021 Emmanouil Benetos, Alessandro Ragano, Daniel Sgroi and Anthony Tuckwell
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.
Culture, Behaviour and Development