Human trafficking is a serious crime that continues to plague the United States. With the rise of computing technologies, the internet has become one of the main mediums through which this crime is facilitated. Fortunately, these online activities leave traces which are invaluable to law enforcement agencies trying to stop human trafficking. However, identifying and intervening with these cases is still a challenging task. The sheer volume of online activity makes it difficult for law enforcement to efficiently identify any potential leads. To compound this issue, traffickers are constantly changing their techniques online to evade detection. Thus, there is a need for tools to efficiently sift through all this online data and narrow down the number of potential leads that a law enforcement agency can deal with. While some tools and prior research do exist for this purpose, none of these tools adequately address law enforcement user needs for information visualizations and spatiotemporal analysis. Thus to address these gaps, this thesis contributes an empirical study of technology and human trafficking. Through in-depth qualitative interviews, systemic literature analysis, and a user-centered design study, this research outlines the challenges and design considerations for developing sociotechnical tools for anti-trafficking efforts. This work further contributes to the greater understanding of the prosecution efforts within the anti-trafficking domain and concludes with the development of a visual analytics prototype that incorporates these design considerations.Ph.D
