Repository Description

This repository contains data for a quantitative analysis of blues lyrics performed by artists across time and socio-cultural groups. This analysis is a part of my PhD project on the use of African American English features as indexical expressions of authenticity in blues music. The particular study for which data is shared here examines the use of African American English (AAE) features in blues music, for which a corpus of 270 studio-performed blues songs was compiled from YouTube, consisting of six songs each by 45 artists. These artists were evenly distributed across three social groups (African American; non-African American, US-based; and non-African American, non-US-based) and three time periods (the 1960s, 1980s, and 2010s). Each artist contributed three original songs and three covers (i.e., previously recorded by other performers). Songs were selected to fit broad blues criteria, including structural, melodic, and lyrical patterns, encompassing traditional blues and contemporary blues-rock. All 270 songs were imported into MAXQDA for transcription and annotation of five phonological and three lexico-grammatical AAE features, selected based on established sociolinguistic literature. Each token where a feature could potentially occur was coded in binary fashion (realized or not), with uncertain cases left uncoded. The annotated data were exported from MAXQDA into a structured tabular format for statistical and machine learning analysis in Python. Only the raw, intermediate and processed datasets are included in this repository. The Python code used to (pre)process and analyze the data are hosted on this GitHub repository.

Article Abstract

Many musicologists and researchers of popular music have recently stressed the omnipresence of covers in today’s music industry. In the sociolinguistics of music, however, studio-recorded covers and their potential differences from ‘original’ compositions have certainly been acknowledged in passing, but very few sociolinguists concerned with the study of song seem to have systematically explored how language use may differ in such re-imagined musical outputs. This article reports on a study which examines the language use of 45 blues artists from three distinct time periods (viz., 1960s, 1980s, and 2010s) and three specific social groups (viz., African American; non-African American, US-based; and non-African American, non-US based) distributed over 270 studio-recorded original and cover performances. Through gradient boosting decision tree classification, it aims to analyze the artists’ use of eight phonological and lexico-grammatical features that are traditionally associated with African American English (viz., /aɪ/ monophthongization, post-consonantal word-final /t/ deletion, post-consonantal word-final /d/ deletion, alveolar nasal /n/ in ultimas, post-vocalic word-final /r/ deletion, copula deletion, third-person singular <s> deletion, and not-contraction). Our analysis finds song type (i.e., the distinction between covers and originals) to have no meaningful impact on artists’ use of the examined features of African American English. Instead, our analysis reveals how performers seem to rely on these features to a great extent and do so markedly consistently, regardless of factors such as time period, socio-cultural background, or song type. This paper hence builds on our previous work on the language use of blues performers by further teasing out the complex indexical and iconic relationships between features of African American English, authenticity, and the blues genre in its various manifestations of time, place, and performance types.

MAXQDA, 24

Python, 3.12.2