Authors - Wonseong Kim Abstract - Geopolitical risk now tends to surface in information environments well before it shows up as physical disruption or moves in market prices, and often before any policy response. Current geopolitical risk indices track the salience of news, and a separate body of work on disinformation detection looks for signals of manipulation. What neither line of work does is connect manipulated discourse to the channels through which food, energy, supply chain, sanctions, and macro-financial risks are actually transmitted. To address this gap, the paper develops a DISARM-informed large language model framework for narrative-based monitoring of disinformation-driven geopolitical risks. The framework is organised as a four-layer architecture that brings together observable manipulation signals, the classification of narrative function, mapping onto risk domains, and the construction of indicators. From these layers it derives interpretable indicators that capture manipulated risk discourse, gaps in framing, concentration of narratives, and transmission across domains. Our central claim is a methodological one: once observable manipulation, narrative function, and risk-domain mapping are represented together, unstructured multilingual media can be turned into auditable early-warning signals. We intend the result as a decision-support instrument for sustainable security monitoring, not as a means of attribution or causal estimation.
Open Zoom