Exploring the Relationship Between the Acoustic Elements of Song and Its Commercial Popularity

Popular music has been observed to follow the trend of commercial homogeneity – the idea that artists take inspiration from a select pool of successful sounds, leading to popular music sounding homogenous.
Hit Song Prediction is a rapidly growing avenue of research in the field of Music Information Retrieval (MIR) that offers promising benefits for the music industry – artists and record labels alike. Hit Song Prediction models analyze trends in popular music through different elements of a song’s composition – acoustic features, lyrical content, environmental factors – and objectively compare new tracks to these trends to determine the likelihood of commercial success. Researchers point to the acoustic compositions of a song as the greatest objective influence on song popularity.

This study explored the correlational relationship between the acoustic features of a song (tempo, RMS energy, Spectral Centroid, Zero Crossing Rate, Major Key Correlation) and its popularity measured by commercial success on Billboard Hot 100 year-end charts. A coded application was written utilizing the Librosa Python program to extract raw data from fifty-five song files from 2021 to 2025 and run correlational analyses.

The results showed that there are weak positive correlations between each of the five evaluated acoustic features and commercial song popularity. This supports the argument that artists should not chase trends during their creative process but rely on alternative methods, such as creativity, as is the method by which music was intended to be created.