@article{THESIS,
      recid = {7267},
      author = {Tang, Ning},
      title = {MUSIC AND SEXUAL IDENTITY: CHANGE IN MUSIC AFTER  SELF-DISCLOSING SEXUAL IDENTITY},
      publisher = {University of Chicago},
      school = {M.A.},
      address = {2023-08},
      number = {THESIS},
      abstract = {Can music reflect the changing nature of sexual identity?  How does the change in the sexual identity of LGBTQ+  representation be performed through music? To address these  ques- tions, this thesis explores the changing performance  of sexual identity through music lyrics. An extensive  examination of LGBTQ+ representation in the music industry  was conducted by compiling data from Spotify playlists. The  sexual identities and self-disclosing dates of 54 selected  artists were identified through manual coding, based on  cross-checked news sources. Subsequently, the lyrics of all  tracks by these artists were scraped from Genius. The  collected data underwent various experiments including  sentiment analysis, topic modeling, cluster- ing, and text  classification techniques to observe changes in sentiment  and topics expressed in the lyrics following the artists’  public disclosure of their sexual identities. Results show  that: (1) the sentiment polarity could change in different  directions depending on the specific characteristics of the  artists; (2) artists express more confidence, more positive  attitude, and stronger love after publicly disclosing their  sexual identities. These findings provide empiri- cal  evidence for the relationship between music and sexual  identity and the impact of sexual identity on music  expression, which addresses a gap in the existing  literature by emphasiz- ing the connection between music  and sexual identity. Furthermore, this study proves that  music could not only reflect sexual identity but also  reflect the dynamic change of sexual identity, which  provides guidance for future studies in music and sexual  identity. The use of computational methods could also  provide some insights for future semantic analysis on a  large corpus of lyrics.},
      url = {http://knowledge.uchicago.edu/record/7267},
      doi = {https://doi.org/10.6082/uchicago.7267},
}