Measuring national mood with music: using machine learning to construct a measure of national valence from audio data

Abstract

We propose a new measure of national valence based on the emotional content of a country’s most popular songs. We first trained a machine learning model using 191 different audio features embedded within music and use this model to construct a long-run valence index for the UK. This index correlates strongly and significantly with survey-based life satisfaction and outperforms an equivalent text-based measure. Our methods have the potential to be applied widely and to provide a solution to the severe lack of historical time-series data on psychological well-being.