Abstract
The ubiquity of digital music consumption has made it possible to extract information about modern music that allows us to perform large scale analysis of stylistic change over time. In order to uncover underlying patterns in cultural evolution, we examine the relationship between the established characteristics of different genres and styles, and the introduction of novel ideas that fuel this ongoing creative evolution. To understand how this dynamic plays out and shapes the cultural ecosystem, we compare musical artifacts to their contemporaries to identify novel artifacts, study the relationship between novelty and commercial success, and connect this to the changes in musical content that we can observe over time. Using Music Information Retrieval (MIR) data and lyrics from Billboard Hot 100 songs between 1974-2013, we calculate a novelty score for each song’s aural attributes and lyrics. Comparing both scores to the popularity of the song following its release, we uncover key patterns in the relationship between novelty and audience reception. Additionally, we look at the link between novelty and the likelihood that a song was influential given where its MIR and lyrical features fit within the larger trends we observed.
| Original language | English (US) |
|---|---|
| Article number | 3 |
| Journal | EPJ Data Science |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2023 |
Funding
The authors would like to thank Miriam Alex for her assistance with data collection and cleaning, and would like to thank Michael Mauskapf and Noah Askin for sharing their unique data set.
Keywords
- Computational methods
- Computational social science
- Cultural novelty
- Quantitative analysis
ASJC Scopus subject areas
- Modeling and Simulation
- Computer Science Applications
- Computational Mathematics