No abstract

For centuries, music has been an inseparable part of many human cultures. The rise of the hip-hop culture over the last 50 years has turned into a powerful movement, empowering people from various communities and making their voices heard. However, certain parts of hip-hop and rap music have started being associated with misogyny, substance abuse and violent behavior. This study aims to find a correlation between lyrics of hip-hop and rap songs that glorify such illicit behavior through their lyrics and the actual rate of criminal activity of individuals that are directly or indirectly influenced by hip-hop culture. This research employs NLP concepts to build a model that detects song lyrics that falls into any of the 3 categories-"Misogyny," "Substance Abuse" and "Violence." A comparative study is conducted by training multiple models including multinomial naïve Bayes, random forest and LSTM on a manually collected and labeled dataset consisting of rap song lyrics released between 1970 and 2020. The highest performing model (LSTM-87% accuracy) was subsequently used to detect objectionable lyrics in popular rap songs of the decade of 2010-2019. To obtain a correlation of these with the criminal activity of the target population, official data of criminal activity (2010-2019) of citizens aged 0-29 from the largest hip-hop influenced areas in the world are compiled. This dataset is analyzed and to obtain strong evidence of a correlation between objectionable rap song lyrics being promoted through song lyrics and the criminal tendencies of the youth that is primarily affected by it.