Date of Award

5-2024

Degree Type

Thesis

Degree Name

Departmental Honors

Department

Mathematics and Statistics

Abstract

This paper examines the correlation between repetitiveness and popularity in the genres of Christian, Country, EDM, Hip-Hop, Latin, Pop, R&B, and Rock. Repetitiveness is defined by the frequency of repeated words in lyrics, and the average number of streams per day defines popularity. This analysis also acknowledges the "popularity" metric provided by Spotify in calculating the correlation. To calculate this correlation, I wrote a program that accesses the Spotify and Genius APIs to gather metadata related to 76,069 songs from 1,246 artists, including data on repetitiveness, tempo, duration, and Spotify's audio metrics of "danceability," "energy," "speechiness," "acousticness," and "instrumentalness." I found a weak correlation between these metrics and popularity, concluding that these metrics are not a reliable predictor of a song's popularity. While the popularity of songs in some genres have a slightly stronger relationship with repetitiveness, such as repetitiveness accounting for 6.1% of the variation of popularity in pop music, there was less of a relationship than I had hypothesized. Understanding these conclusions and considering external factors that influence the popularity of a song can help artists understand what they must do to influence their song's appearance on the charts.

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Faculty Mentor

Daniel Coster

Departmental Honors Advisor

David Brown