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

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...

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Detalles Bibliográficos
Autores principales: Benetos, Emmanouil, Ragano, Alessandro, Sgroi, Daniel, Tuckwell, Anthony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8876081/
https://www.ncbi.nlm.nih.gov/pubmed/35212936
http://dx.doi.org/10.3758/s13428-021-01747-7
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.3758/s13428-021-01747-7.