@TechReport{iza:izadps:dp14258,
            	author={Benetos, Emmanouil and Ragano, Alessandro and Sgroi, Daniel and Tuckwell, Anthony},
            	title={Measuring National Life Satisfaction  with Music},
            	year={2021},
	month={Apr},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={14258},
            	url={https://www.iza.org/publications/dp14258},
	abstract={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.},
	keywords={historical subjective wellbeing;life satisfaction;music;sound data;language;big data},
            }