# Decoding the Style and Bias of Song Lyrics

## TL;DR

This paper computationally analyzes over half a million song lyrics to understand their style and biases, revealing societal reflections and differences between popular and other songs.

## Contribution

It introduces a large-scale analysis of song lyrics focusing on style and bias, utilizing distributed representations and bias measurement tests.

## Key findings

- Popular songs have distinct style characteristics.
- Lyrics reflect societal gender and racial biases.
- Biases in lyrics correlate with societal biases.

## Abstract

The central idea of this paper is to gain a deeper understanding of song lyrics computationally. We focus on two aspects: style and biases of song lyrics. All prior works to understand these two aspects are limited to manual analysis of a small corpus of song lyrics. In contrast, we analyzed more than half a million songs spread over five decades. We characterize the lyrics style in terms of vocabulary, length, repetitiveness, speed, and readability. We have observed that the style of popular songs significantly differs from other songs. We have used distributed representation methods and WEAT test to measure various gender and racial biases in the song lyrics. We have observed that biases in song lyrics correlate with prior results on human subjects. This correlation indicates that song lyrics reflect the biases that exist in society. Increasing consumption of music and the effect of lyrics on human emotions makes this analysis important.