The outbreak of coronavirus disease 2019 (COVID-19) was highly stressful for people. In general, fear and anxiety about a disease can be overwhelming and cause strong emotions in adults and children. One way to cope with this stress consists in listening to music. Aim of this work is to understand if the music heard during the lock-down reflects the emotions generated by the pandemic on each of us. So, the primary goal of this work is to build two indices for measuring the anger and joy levels of the top streamed songs by Italian Spotify users (during the SARS-CoV-2 pandemic), and study their evolution over time. A Hierarchical Cluster Analysis has been applied in order to identify groups of weeks reflecting common musical sentiments, and a Beta regression model is used to validate the results of cluster analysis.

Alessandro Albano, M.S. (2021). Impact of the COVID-19 pandemic on music: a method for clustering sentiments. In Book of Short Papers of the 5th international workshop on Models and Learning for Clustering and Classification.

Impact of the COVID-19 pandemic on music: a method for clustering sentiments

Alessandro Albano
;
Mariangela Sciandra;Antonella Plaia;Irene Carola Spera
2021-10-01

Abstract

The outbreak of coronavirus disease 2019 (COVID-19) was highly stressful for people. In general, fear and anxiety about a disease can be overwhelming and cause strong emotions in adults and children. One way to cope with this stress consists in listening to music. Aim of this work is to understand if the music heard during the lock-down reflects the emotions generated by the pandemic on each of us. So, the primary goal of this work is to build two indices for measuring the anger and joy levels of the top streamed songs by Italian Spotify users (during the SARS-CoV-2 pandemic), and study their evolution over time. A Hierarchical Cluster Analysis has been applied in order to identify groups of weeks reflecting common musical sentiments, and a Beta regression model is used to validate the results of cluster analysis.
Settore SECS-S/01 - Statistica
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Alessandro Albano, M.S. (2021). Impact of the COVID-19 pandemic on music: a method for clustering sentiments. In Book of Short Papers of the 5th international workshop on Models and Learning for Clustering and Classification.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/524502
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