Data Mining for Sustainable Urban Safety: Uncovering Patterns in Mass Killings for Safer Communities
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Chigozie Ofodike
College:
The Dorothy and George Hennings College of Science, Mathematics, and Technology
Major:
Computer Science
Faculty Research Advisor(s):
Ching-yu Huang
Abstract:
This study delves into the complexities of mass killings in the United States, leveraging data from multiple gun violence databases. Examining incidents with three or more fatalities excluding the perpetrator as "mass killings," this analysis reveals a deeply troubling trend: 2019 saw the highest number of such events since the 1970s, with mass shootings constituting the majority. While family annihilations remained the most frequent type, public mass shootings, although less common, have become alarmingly more frequent since 2011. This research employs interactive visualizations and in-depth analysis exploring mass killings' temporal and typological distribution nationwide. By highlighting the rise in public mass shootings and limitations in gun violence research, this study emphasizes the need for comprehensive, data-driven research that transcends political agendas. This research can influence policy interventions prioritizing safety and well-being, ultimately contributing to curbing this national epidemic.
Keywords: Mass killings, mass shootings, family annihilations, gun violence, United States, trends, data analysis, gun research, gun control, mental health.