Functional diversity in human song
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View abstract on PubMed
Summary
This summary is machine-generated.Functional diversity, the variety of species traits, can predict music popularity. Higher sonic variety in an artist's songs correlates with millions more listens and significant profit gains.
Area Of Science
- Ecology
- Musicology
- Computational Social Science
Background
- Functional diversity, the range of traits within a community, has transformed ecological studies from species-focused to ecosystem-focused.
- While established in ecology, its application to other fields like music remains underexplored.
Purpose Of The Study
- To adapt and apply functional diversity metrics to music analysis.
- To investigate the relationship between musical functional diversity and artist popularity on streaming platforms.
Main Methods
- Collected data on 14 musical characteristics for 12,944 songs from top artists of the 2010s.
- Calculated functional diversity (richness, evenness, divergence) using probabilistic hypervolumes.
- Correlated diversity metrics and song/artist traits with streaming platform popularity (listens).
Main Results
- High functional richness (sonic variety) significantly increased song listens (up to 244.3 million) and potential earnings (over $1 million per gain).
- Danceable, energetic, melodic, pop, and melancholic music attributes showed higher listenership.
- Musical patterns may reflect societal moods and trends.
Conclusions
- Functional diversity metrics can be applied beyond ecology, offering insights into music industry economics and cultural trends.
- Musical functional diversity is a significant predictor of an artist's commercial success.
- This interdisciplinary approach simplifies complex ecological concepts using music as a relatable case study.
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