Betti, LorenzoAbrate, CarloKaltenbrunner, Andreas2023-06-302023-06-302023Betti L, Abrate C, Kaltenbrunner A. Large scale analysis of gender bias and sexism in song lyrics. EPJ Data Sci. 2023;12:10. DOI: 10.1140/epjds/s13688-023-00384-82193-1127http://hdl.handle.net/10230/57420We employ Natural Language Processing techniques to analyse 377,808 English song lyrics from the “Two Million Song Database” corpus, focusing on the expression of sexism across five decades (1960–2010) and the measurement of gender biases. Using a sexism classifier, we identify sexist lyrics at a larger scale than previous studies using small samples of manually annotated popular songs. Furthermore, we reveal gender biases by measuring associations in word embeddings learned on song lyrics. We find sexist content to increase across time, especially from male artists and for popular songs appearing in Billboard charts. Songs are also shown to contain different language biases depending on the gender of the performer, with male solo artist songs containing more and stronger biases. This is the first large scale analysis of this type, giving insights into language usage in such an influential part of popular culture.application/pdfeng© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/articlehttp://dx.doi.org/10.1140/epjds/s13688-023-00384-8Song lyricsGenderNatural language processingWord embeddingsLanguage biasSexisminfo:eu-repo/semantics/openAccess