OSINT Research Project Paper

OSINT Collection Plan for Identifying Human Trafficking Indicators on Social Media in Kenya Introduction Social media and digital communication have upended the world of human trafficking. Organized crime is using such platforms to recruit, communicate across networks and advertise illicit services with an unprecedented speed and volume (UNODC 2021). The objective of the study is to design a sustainable Open Source Intelligence (OSINT) collection plan on social media that can pick on human trafficking signals, with particular reference in Kenya. This work will use modern social media analysis tools to collect openly available data. The overarching aim is to not only identify recruitment advertisements but to understand social media user attitudes towards child trafficking. In particular, attention is paid to the community-produced alerts, lived experience accounts, and encoded narratives that uncover the mechanics of internet human-traffickers. This study seeks to fill an important void in intelligence analysis through the use of thematic qualitative analysis and data triangulation. Background of the Study Kenya is a major source, transit, and destination country for trafficking in persons including for the purposes of forced labor and sexual exploitation (U.S. Department of State's Trafficking in Persons Report Country Narrative, 2023). The downward spiral of vulnerability is notably striking among women and girls from Kenya who are increasingly enticed with fraudulent online advertisements for high-paying work in the Gulf States or elsewhere abroad (UNODC, 2021). This online recruitment ruse turns the internet into a means of exploitation, compromising the safety and security of young people who typically use social media more than adult counterparts. Acknowledging these transitions, the government of Kenya has admitted that social media platforms have become a strategically new front for combating human traffickers. The main lack of understanding in intelligence is the absence of a structured understanding of the indigenous, user-generated indicators in the Kenyan social media space. In order to know detect the signs that something suspicious is definitely happening, law enforcement have Local contextualisation detections of online activities. The Priority Information Requirement or ‘PIR’ should be as follows: what are the current social media narratives, coded language (including Swahili/Sheng terms), and user-generated warnings that suggest the recruitment and exploitation of Kenyan youth for forced labor or sexual exploitation? OSINT Collection Plan Steps The collection plan follows the fundamental intelligence cycle, ensuring the process is systematic, repeatable, and focused on addressing the PIR. Direction and Planning The initial phase defines the scope and methodology. The focus is on platforms popular in Kenya for job-seeking and community discussions, such as Facebook, X (formerly Twitter), and public WhatsApp/Telegram group link aggregators. Keyword development is critical and must extend beyond explicit terms to include euphemisms and coded language related to various key terms. Some of the terms for deceptive employment include Kuomba job (to look for a job), mshahara mzuri (good salary), agent, Gulf work, visa assist, and househelp. For control and coercion, the keywords are passport kwangu (passport with me), deni (debt), and kukosa simu (no phone access). The planning also includes location and victim profiling with terms related to Nairobi, Mombasa, and high-risk recruitment zones. Collection and Exploitation Collection will be facilitated by automated social media analytics solutions that are able to scrape and filter large amounts of public posting based upon the specified key words and geographical filters. The main data resources are going to be posts, comments, shares, published user profiles. For mass data collection tools, it will include such tools as Brandwatch (or similar commercially developed interfaces) to run structured queries across massive historical and real-time social media streams (Brandwatch, 2024). That gives the scope of data required to detect broad trends and volume spikes when it comes to recruitment. The team will also gather information through network mapping. In other words, information would be pulled from Brandwatch (or X/Facebook via their API) and flows into NodeXL. This network visualization tool en...