Anglada-Tort, Manuel; Krause, Amanda E and North, Adrian C. 2021. Popular music lyrics and musicians’ gender over time: A computational approach. Psychology of Music, 49(3), pp. 426-444. ISSN 0305-7356 [Article]

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Abstract or Description

The present study investigated how the gender distribution of the United Kingdom’s most popular artists has changed over time and the extent to which these changes might relate to popular music lyrics. Using data mining and machine learning techniques, we analyzed all songs that reached the UK weekly top 5 sales charts from 1960 to 2015 (4,222 songs). DICTION software facilitated a computerized analysis of the lyrics, measuring a total of 36 lyrical variables per song. Results showed a significant inequality in gender representation on the charts. However, the presence of female musicians increased significantly over the time span. The most critical inflection points leading to changes in the prevalence of female musicians were in 1968, 1976, and 1984. Linear mixed-effect models showed that the total number of words and the use of self-reference in popular music lyrics changed significantly as a function of musicians’ gender distribution over time, and particularly around the three critical inflection points identified. Irrespective of gender, there was a significant trend toward increasing repetition in the lyrics over time. Results are discussed in terms of the potential advantages of using machine learning techniques to study naturalistic singles sales charts data.

Item Type:	Article
Identification Number (DOI):	https://doi.org/10.1177/0305735619871602
Additional Information:	Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially supported by a PhD studentship from the “Studienstiftung des Deutschen Volkes” (Bonn, Germany) awarded to Manuel Anglada-Tort.
Keywords:	popular music, lyrics, gender, DICTION, sales charts, machine learning
Departments, Centres and Research Units:	Psychology
Dates:	Date Event 23 October 2019 Published Online May 2021 Published
Item ID:	36636
Date Deposited:	12 Jun 2024 10:07
Last Modified:	12 Jun 2024 10:09
Peer Reviewed:	Yes, this version has been peer-reviewed.
URI:	https://research.gold.ac.uk/id/eprint/36636

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