Predicting the Likelihood of Mass Shootings in a Location Using Prominent Risk Factors

Authors

  • Nishanth Srinivasan Little Rock Central High School

Abstract

Mass shootings are incidents in which 4 or more casualties - injuries or deaths - have occurred due to gun violence. If the shooting has 4 or more deaths, then it is considered a major mass shooting. These mass shootings have become a significant problem in the United States in the past few years with over 600 incidents in just 2022, resulting in over 700 deaths and around 3000 injuries (Gun Violence Archive, 2023). Additionally, in the first 4 months of 2023, over 150 mass shootings have happened in the United States at a rate of about 1.5 shootings per day (Gun Violence Archive, 2023). Despite the largely frequent occurrences of these shootings in American society, the government has taken very little action to prevent these mass shootings from occurring. While part of this is because of the widely varying ideals on gun control on the different sides of the political spectrum (Braga, 2001), a large part of this inaction is also due to the unpredictability of these mass shootings (Duwe et al., 2022). Even though mass shootings happen quite often, they are erratic in their nature which makes it hard to observe patterns among them. However, if someone were to create a way to easily predict the odds of the occurrence of these mass shootings using certain factors that are noticeable, this could allow the public to understand apparent patterns in mass shooting occurrence and help the government create legislation to help prevent future mass shootings. Thus, this study aims to develop a predictive model to assess the likelihood of mass shootings based on key socio-economic and geographic factors. By identifying high-risk cities, this model could provide policymakers with tools to implement targeted preventive measures. To approach this serious topic of mass shootings and learn more about these potential factors, the history of these shootings must first be examined.

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Published

2025-04-09

Issue

Section

Research Articles