Leveraging Publicly Available Data to Discern Patterns of Human-Trafficking Activity

Authors: Dubrawski, Artur; Miller, Kyle; Barnes, Matthew; Boecking, Benedikt & Kennedy, Emily

Abstract: We present a few data analysis methods that can be used to process advertisements for escort services available in public areas of the Internet. These data provide a readily available proxy evidence for modeling and discerning human-trafficking activity. We show how it can be used to identify advertisements that likely involve such activity. We demonstrate its utility in identifying and tracking entities in the Web-advertisement data even if strongly identifiable features are sparse. We also show a few possible ways to perform community- and population-level analyses including behavioral summaries stratified by various types of activity and detection of emerging trends and patterns.

Keywords: escort advertisements, human trafficking, machine learning, pattern mining, prostitution