Data Collection and Analysis for Small-Town Policing: Challenges and Recommendations

Abstract

According to the 2020 U.S. Census more than 60% of the U.S. population lives in towns with fewer than 50,000 residents, yet this is not in proportion with the research and public data surrounding policing, which focus on large and dense urban areas. One reason for this disparity is that studying small-town police departments presents unique obstacles. We present some of the challenges that we have encountered in studying small-town police activity such as data availability, quality, and identifiability, and our solutions to these challenges using computational tools. Finally, we give our recommendations in getting involved in this space based on our efforts to-date.

Keywords

• Data science
• Natural language processing
• Police reform
• Quantitative social justice
• Small-town
• Spatial statistics