14: Impact of Arrests on Human Trafficking Ad Volume Using a Nonparametric Change-Point Model

Music City Center 

Human trafficking is a critical issue, with online advertisements serving as proxies for illicit activity within the trafficking network. Law enforcement works diligently to disrupt the networks, but long-term effectiveness of arrests on reducing online advertisements is unclear. Existing research highlights immediate impacts of law enforcement intervention but lacks consensus on sustained reductions. This study explores the relationship between arrests and fluctuations in trafficking ads using data from five cities. By analyzing time-series data, we investigate whether arrests trigger significant changes in ad volumes and identify potential changepoints associated with enforcement activity. Descriptive statistics reveal short-term declines in ad activity following arrests, though long-term patterns are ambiguous. Applying a nonparametric changepoint model, we observe short-term decreases but limited evidence for lasting impact on ad activity. These findings suggest that while arrests disrupt trafficking activity, they may not produce sustained reductions. This research emphasizes the importance of date-informed strategies and coordinated interventions to combat human trafficking.

Nonparametric Changepoint Model

Time Series Analysis

Law Enforcement Impact

Human Trafficking 

Section on Nonparametric Statistics