US Fatal Police Shooting Analysis and Prediction

TL;DR

This paper applies multidimensional statistical analysis to understand and predict US fatal police shootings, revealing key factors and testing for racial discrimination with high predictive accuracy.

Contribution

It introduces a new method to quantify media reporting deviations, analyzes comprehensive datasets with pattern mining and clustering, and develops models to predict shooting rates and victim race.

Findings

Police shooting rate depends on multiple variables like land area and gun ownership.

Best regression model predicts shooting rates with 88.53% correlation.

No significant evidence of racial discrimination in fatal shootings.

Abstract

We believe that "all men are created equal". With the rise of the police shootings reported by media, more people in the U.S. think that police use excessive force during law enforcement, especially to a specific group of people. We want to apply multidimensional statistical analysis to reveal more facts than the monotone mainstream media. Our paper has three parts. First, we proposed a new method to quantify fatal police shooting news reporting deviation of mainstream media, which includes CNN, FOX, ABC, and NBC. Second, we analyzed the most comprehensive US fatal police shooting dataset from Washington Post. We used FP-growth to reveal the frequent patterns and DBSCAN clustering to find fatal shooting hotspots. We brought multi-attributes (social economics, demographics, political tendency, education, gun ownership rate, police training hours, etc.) to reveal connections under the iceberg. We found that the police shooting rate of a state depends on many variables. The top four most relevant attributes were state joined year, state land area, gun ownership rate, and violent crime rate. Third, we proposed four regression models to predict police shooting rates at the state level. The best model Kstar could predict the fatal police shooting rate with about 88.53% correlation coefficient. We also proposed classification models, including Gradient Boosting Machine, Multi-class Classifier, Logistic Regression, and Naive Bayes Classifier, to predict the race of fatal police shooting victims. Our classification models show no significant evidence to conclude that racial discrimination happened during fatal police shootings recorded by the WP dataset.