Author(s) :

Ruoqing Huang.

Volume/Issue :

Abstract :

This study examines how audio features influence the popularity of songs on Spotify, focusing on tracks that have appeared on the Billboard Year-End Hot 100 charts. Using data from both Billboard and Spotify, the analysis explores the relationship between features such as Energy, Danceability, Loudness, and Instrumentalness and their impact on Spotify's Popularity scores. Correlation and regression models, ensemble learning, and clustering techniques were applied to uncover patterns and insights. Results show that high-energy, danceable, and loud songs tend to achieve higher popularity, while quieter and more experimental tracks are often less favored. Dimensionality reduction and clustering methods identified groups of songs with distinct audio profiles, highlighting the characteristics associated with varying levels of engagement. This research provides insights into the role of audio features in shaping song popularity, offering useful information for artists, producers, and industry professionals.