OPEN-SOURCE INTELLIGENCE APPLICATIONS IN REAL-TIME GEOPOLITICAL ANALYSIS: A DATA-DRIVEN APPROACH

Abstract

The increasing complexity of the global security landscape has generated substantial demand for tools capable of processing and visualizing geopolitical intelligence in real time. Open-Source Intelligence (OSINT), defined as the systematic collection and analysis of publicly available data, has emerged as a foundational methodology in modern geopolitical risk assessment. This paper examined the role of data-driven OSINT applications in supporting situational awareness and geopolitical analysis, with a focus on the Global Threat Map , an open-source intelligence platform developed by Prosper Otemuyiwa and released publicly in January 2026. Through a combination of theoretical framing, architectural analysis, and critical evaluation, this study assessed the platform's capacity to aggregate, classify, and visualize geopolitical events at scale. The application integrates real-time data ingestion via the Valyu AI intelligence API, geospatial rendering through Mapbox GL JS, and AI-assisted synthesis of country-level conflict profiles, enabling analysts to monitor armed conflicts, diplomatic incidents, protests, and military developments on an interactive world map. The findings indicated that data-driven OSINT dashboards represent a significant step toward democratizing geopolitical intelligence, though persistent challenges related to data provenance, AI-generated content reliability, source opacity, and the absence of structured validation frameworks remain critical limitations. The paper concluded by identifying directions for future development, particularly regarding multi-source data triangulation, explainability mechanisms, and integration with verified open datasets such as ACLED and GDELT.