Hidden in Plain Sight: A Machine Learning Approach for Detecting Prostitution Activity in Phoenix, Arizona

摘要: Prostitution has been a topic of study for decades, yet many questions remain about where prostitution occurs. Difficulty in identifying activity is often attributed to the hidden and seemingly victimless nature crime. Despite numerous challenges associated with policing street prostitution, these encounters become more difficult identify when they take place indoors, especially locations away from public view, such as hotels. The purpose this paper develop strategy hotel facilities surrounding areas that may be experiencing elevated levels using high-volume, user-generated data, namely reviews written by guests posted Travelocity.com. A unique synthesis methods including data mining, natural language processing, machine learning, basic spatial analysis are combined require additional law enforcement resources and/or social/health service outreach. hotspots identified within city Phoenix, Arizona policy implications discussed.