In 2025, the project further developed a framework for disinformation research by integrating societal analysis, advanced artificial intelligence, and outcomes related to policy making. The analysis identified population groups particularly vulnerable to disinformation, including elderly people, minorities, immigrant communities, and geographically or educationally disadvantaged groups, showing how exposure, susceptibility, and impact vary across contexts.
The research applied narrative analysis, discourse analysis, forensic linguistics, and case-study methods to examine how foreign interference campaigns exploit polarizing themes linked to geopolitics, climate change, and identity. Profiling of state and private actors provided context within European strategic communication and cybersecurity frameworks. Research outputs were translated into working papers and policy briefs to support technological work and policy making.
From a technological perspective, the work combines curated, fact-checked multimodal datasets with machine learning and semantic knowledge representation. Linguistic, visual, and auditory features are embedded into web-standard-based knowledge graphs, enabling explainable analysis, semantic querying, and human-in-the-loop adaptation. A modular multimodal AI architecture has been integrating similarity analysis, deepfake detection, and cross-modal coherence checking to generate an interpretable probabilistic disinformation score supported by trustworthy AI methods.
User-centered, ethical, and inclusive design principles are being embedded in the work. Multilingual surveys, beta testing with real-world cases, and multi-stakeholder focus groups assess public perception, trust, and resilience, while gender, equity, and bias analyses support tool development.
