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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 add our two cents point of view by multidimensional analysis to reveal more facts than the monotone mainstream media. The more facets we understand the problem, the better solution that the whole society could approach.
- Introduction
Our report has three parts: First, we analyzed and quantified fatal police shooting news reporting deviation of mainstream media. Second, we used FP-growth to mine frequent patterns, clustered hotspots of fatal police shootings, and brought multi-attributes (social economics, demographics,
political tendency, education, gun ownership rate, police training hours, etc.) to reveal connections under the iceberg. Third, we built regression models based on correlation analysis for numeric variables selection to predict police shooting rates at the state level. We also built classification models based on Chi-square testing for categorical variables selection to predict the victims’ race of fatal police shootings. The main datasets we choose for our analysis include:- 1.Washington Post Fatal Police Shooting Dataset (WP data) covers fatal police shooting from 01-01-2015 to 12- 02-2020.
- 2. KilledByPolice (KBP): Fatal police shooting reported in KilledByPolice website from 01-01-2015 to 11-04-2020
- Related work
Several studies have been conducted based on utilizing local crime data to explain racial disparities and differences in fatal police shootings. Mentch (2020) implemented resampling procedures to take factors like local arrest demography and law enforcement density into account. He found substantially less racial disparity after accounting for local arrest demographics. On the contrary, Ross (2015) built a multi-level Bayesian model to investigate the extent of racial bias in the recent shooting of civilians by police. He concluded that racial discrimination observed in police
shootings is not explainable due to local-level race-specific crime rates. Noticeably, Mentch and Ross had reached contradictory conclusions. But they inspired us to use data mining and machine earning techniques to incorporate more factors rather than only crime data to understand fatal police shootings in the US better.
