Bringing Efficiencies to Criminal Justice Manual Coding through Machine Learning

Criminal justice research can often require conversion of open-ended, free-text offense descriptions into overall charge categories to aid analysis. For example, the free-text offense of "eluding a police vehicle" would be coded to a charge category of "Obstruction - Law Enforcement". Since free-text offense descriptions aren't standardized and often need to be categorized in large volumes, this can result in a manual and time intensive process for researchers. Using publicly available national data to train a machine learning model, we present a web application allowing for the bulk conversion of offense text stored in common formats (e.g., XLSX, CSV) into offense categories used in criminal justice. This results in the reduction of an hours-long coding task to minutes with an overall accuracy of 93%.

Machine Learning

Criminal Justice

Natural Language Processing

Web Application

Python

Open Text 

Mid-Level

Knowledge

Women in Statistics and Data Science 2022