The rhetoric of de-policing: Evaluating open-ended survey responses from police officers with machine learning-based structural topic modeling

Abstract

The study extracts latent topic models from open-ended survey responses and tests the relationship between the resulting models and police officers' motivation to engage in proactive policing. Using structural topic modeling, a type of unsupervised machine learning-based text analysis, the study demonstrates how researchers can gain additional insight into police attitudes. The analysis establishes topics of Professionalism and Distortion as significant predictors of proactivity sentiments, while Naivety has no significant association.