1-19 - Pandemics, Music, and Collective Sentiment: Evidence from the Outbreak of COVID-19
Meijun Liu, Eva Zangerle, Xiao Hu, Alessandro Melchiorre, Markus Schedl
Keywords: Applications, Music retrieval systems, Music and health, well-being, and therapy, Music recommendation and playlist generation, Musical features and properties, Musical affect, emotion, and mood
Abstract:
The COVID-19 pandemic causes a massive global health crisis and produces substantial economic and social distress, which in turn may cause stress and anxiety among people. Real-world events play a key role in shaping collective sentiment in a society. As people listen to music daily everywhere in the world, the sentiment of music being listened to can reflect the mood of the listeners and serve as a measure of collective sentiment. However, the exact relationship between real-world events and the sentiment of music being listened to is not clear. Driven by this research gap, we use the unexpected outbreak of COVID-19 as a natural experiment to explore how users' sentiment of music being listened to evolves before and during the outbreak of the pandemic. We employ causal inference approaches on an extended version of the LFM-1b dataset of listening events shared on Last.fm, to examine the impact of the pandemic on the sentiment of music listened to by users in different countries. We find that, after the first COVID-19 case in a country was confirmed, the sentiment of artists users listened to becomes more negative. This negative effect is pronounced for males while females' music emotion is less influenced by the outbreak of the COVID-19 pandemic. We further find a negative association between the number of new weekly COVID-19 cases and users' music sentiment. Our results provide empirical evidence that public sentiment can be monitored based on collective music listening behaviors, which can contribute to research in related disciplines.