Are Expressions for Music Emotions the Same Across Cultures?
This work addresses the issue of biased emotion descriptors in cross-cultural music research, which is incremental as it builds on existing debates by proposing a new methodological approach.
The study tackled the problem of cultural bias in music emotion research by conducting experiments in Brazil, the US, and South Korea with 672 participants, finding consistency in high arousal and valence emotions but variability in others, and highlighting inadequacies in machine translations for capturing music-specific meanings.
Music evokes profound emotions, yet the universality of emotional descriptors across languages remains debated. A key challenge in cross-cultural research on music emotion is biased stimulus selection and manual curation of taxonomies, predominantly relying on Western music and languages. To address this, we propose a balanced experimental design with nine online experiments in Brazil, the US, and South Korea, involving N=672 participants. First, we sample a balanced set of popular music from these countries. Using an open-ended tagging pipeline, we then gather emotion terms to create culture-specific taxonomies. Finally, using these bottom-up taxonomies, participants rate emotions of each song. This allows us to map emotional similarities within and across cultures. Results show consistency in high arousal, high valence emotions but greater variability in others. Notably, machine translations were often inadequate to capture music-specific meanings. These findings together highlight the need for a domain-sensitive, open-ended, bottom-up emotion elicitation approach to reduce cultural biases in emotion research.