Examining UK drill music through sentiment trajectory analysis
This provides empirical insights for researchers and policymakers to better understand the alleged link between drill music and youth violence in London, though it is incremental as it applies existing NLP techniques to a new domain.
The paper tackled the problem of analyzing sentiment trajectories in UK gang-related drill music lyrics to understand their patterns and impact, finding that lyrics with a positive tone attract more YouTube views and engagement than negative ones.
This paper presents how techniques from natural language processing can be used to examine the sentiment trajectories of gang-related drill music in the United Kingdom (UK). This work is important because key public figures are loosely making controversial linkages between drill music and recent escalations in youth violence in London. Thus, this paper examines the dynamic use of sentiment in gang-related drill music lyrics. The findings suggest two distinct sentiment use patterns and statistical analyses revealed that lyrics with a markedly positive tone attract more views and engagement on YouTube than negative ones. Our work provides the first empirical insights into the language use of London drill music, and it can, therefore, be used in future studies and by policymakers to help understand the alleged drill-gang nexus.