​​SOCIAL MEDIA INTELLIGENCE (SOCMINT) INVESTIGATIVE FRAMEWORK ​AS A HUMAN TRAFFICKING DETERRENT TOOL​

Open-source intelligence is utilized to identify individuals and compare changes in social media profiles and content. The proliferation of social media platforms and apps has facilitated the creation, distribution, and consumption of material related to human trafficking. Social media and internet service providers are not obligated to monitor users for trafficking-related activities or content.

However, an increase in minors joining social media leads to a rise in predatory activity. With the escalation of predatory behavior, research can focus on communication patterns, grooming, and victim profiles targeted by criminals. Technology has been developed to identify biometric points, aiding the identification of victims and criminals. Open-source intelligence is just one step toward gathering information about victims and criminals. It can be utilized throughout the investigative process to prevent human trafficking and related crimes.

This research employs open-source intelligence to provide investigators, law enforcement, and government agencies with preventative solutions for this global issue. The study focuses on extracting, collecting, and analyzing social media and OSINT, specifically social media intelligence (SOCMINT). Classification patterns were identified, and suspicious behavior indicative of human trafficking was detected using the JAPAN principle approach, reducing information overload.

Additionally, the research introduced a standardized investigation framework based on gathered data. This framework demonstrated the effectiveness of selected SOCMINT tools in enhancing human trafficking investigations. The study emphasizes the need for adaptive tools in SOCMINT, complemented by innovative approaches, to strengthen law enforcement efforts in deterring human trafficking.