Decoding The Style And Bias of Song Lyrics

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.

[1]  Thierry Bertin-Mahieux,et al.  The Million Song Dataset , 2011, ISMIR.

[2]  Peter Knees,et al.  A survey of music similarity and recommendation from music context data , 2013, ACM Trans. Multim. Comput. Commun. Appl..

[3]  Andreas Rauber,et al.  Rhyme and Style Features for Musical Genre Classification by Song Lyrics , 2008, ISMIR.

[4]  Michael Fell,et al.  Lyrics-based Analysis and Classification of Music , 2014, COLING.

[5]  Laura B. Doering,et al.  The Effects of Gendered Occupational Roles on Men’s and Women’s Workplace Authority: Evidence from Microfinance , 2017 .

[6]  Edward Sapir,et al.  Selected Writings of Edward Sapir in Language, Culture and Personality , 1950 .

[7]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[8]  Amit Awekar,et al.  It's Only Words And Words Are All I Have , 2019, ECIR.

[9]  Arvind Narayanan,et al.  Semantics derived automatically from language corpora contain human-like biases , 2016, Science.

[10]  Tomas Mikolov,et al.  Enriching Word Vectors with Subword Information , 2016, TACL.

[11]  Rebecca L. Densley,et al.  Girl in a Country Song: Gender Roles and Objectification of Women in Popular Country Music across 1990 to 2014 , 2017 .

[12]  A. Greenwald,et al.  Measuring individual differences in implicit cognition: the implicit association test. , 1998, Journal of personality and social psychology.

[13]  Tobias Greitemeyer Effects of songs with prosocial lyrics on prosocial thoughts, affect, and behavior. , 2009 .

[14]  Craig A Anderson,et al.  Exposure to violent media: the effects of songs with violent lyrics on aggressive thoughts and feelings. , 2003, Journal of personality and social psychology.

[15]  J. West,et al.  Sexualization in Lyrics of Popular Music from 1959 to 2009: Implications for Sexuality Educators , 2012 .

[16]  Joseph C. Nunes,et al.  The power of repetition: repetitive lyrics in a song increase processing fluency and drive market success , 2015 .

[17]  R. P. Fishburne,et al.  Derivation of New Readability Formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) for Navy Enlisted Personnel , 1975 .