Public discourse in the aftermath of the 2022 mass shooting in Buffalo, NY: Insights from social media data and ChatGPT

Recent studies highlight the importance of transformative changes in planning and policymaking to enhance collaboration and effectiveness using new data sources and advanced tools. This study examines the potential of the NLP application in urban planning and the limitations of social media data in capturing local community concerns. Mass shootings have surged dramatically in the U.S., becoming alarmingly common, a troubling trend that is also evident globally. We investigated the dominant semantic topics and sentiments on Twitter about Buffalo's racially segregated East Side neighborhoods since the 2022 mass shooting, using natural language processing (NLP) and ChatGPT. The findings reveal a shift in discussions toward the shooter and broader issues of racism, rather than structural inequalities and local conditions in the Black community. Tweets primarily expressed sadness and anger, but also advocacy. Effective policy-making, such as post-massacre gun control, may have influenced social media discussions. At the same time, the government's failure to address structural racism and deliver promised improvements may create a disconnection between community needs and their online representations.