Quantile Regression Approach in Analysis of Factors Affecting Song Popularity

The music industry generates huge revenue from songs. While various studies have been carried out to predict the popularity of the songs, to the best of our knowledge, this is the first study that employs quantile regression, which analyzes various quantiles of data containing songs and the various factors that contribute to their popularity. The analysis may help various songwriters, artists, music industries, and producers determine which types of songs have a higher probability of becoming popular. The high preference of the audience for the song makes a song popular in society. Quantile regression at the 0.10, 0.25, 0.50, 0.75, and 0.90 quantiles is taken to understand the relationship between song popularity and various factors affecting it such as song duration, liveness, acoustics, tempo, danceability, loudness, and others. This may help the music industry do commercial analysis to determine how various factors contribute to making a song popular.