Web: http://arxiv.org/abs/2208.02052

Aug. 5, 2022, 1:11 a.m. | Lorenzo Betti, Carlo Abrate, Andreas Kaltenbrunner

cs.CL updates on arXiv.org arxiv.org

We employ Natural Language Processing techniques to analyse 377808 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 …

analysis arxiv bias cross gender gender bias scale sexism

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