Human Trafficking Through Data Sharing and Analytics

Human trafficking remains a defining issue in the 21st century. Analytics in human trafficking is explored to examine the existing methods used to combat the problem. A systematic approach of reviewing the related works is adopted, investigating each element within the definition of human trafficking, analytics techniques adopted by previous studies and the analysis of the related works. The analytics techniques were categorized into machine learning and statistical analysis. Significant findings in this paper include: (1) Most of the previous studies explored sexual exploitation using machine learning and statistical analysis; (2) In machine learning, classification algorithms were widely used; (3) In statistical analysis, data sampling methods were commonly applied; and (4) No machine learning method was found to detect forced labor, which remains an area that needs to be further explored.