The authors 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.
The authors show how such data analysis can be used to identify advertisements that likely involve such activity. They demonstrate its utility in identifying and tracking entities in the Web-advertisement data even if strongly identifiable features are sparse. They 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. (Published abstract provided)