Type:
Event

SITE Seminar | Propaganda and disinformation as components of hybrid warfare: The case of the Russian–Ukrainian war

Join us for the next SITE Seminar! On May 5, 2026, we welcome Nina Khairova to discuss how misinformation escalates into coordinated propaganda campaigns in digital environments, and what this implies for detecting manipulative information in the context of hybrid warfare. The seminar introduces a framework for AI-based misinformation detection and uses the Russian–Ukrainian war as a case study to illustrate why context-aware approaches are essential.

Working paper title: Propaganda and Disinformation as Components of Hybrid Warfare: The Case of the Russian–Ukrainian War

By: Nina Khairova

Abstract

The rapid spread of misinformation in digital environments has intensified the need for systematic approaches to understanding and detecting manipulative information. This presentation examines the escalation from false or misleading information to persuasive propaganda, highlighting how narratives evolve from isolated inaccuracies into coordinated influence campaigns. Particular attention is given to the technical and psychological foundations that contribute to the effectiveness of propaganda, including strategic framing, emotional triggers, and the exploitation of cognitive biases.

Building on these insights, the talk introduces a general framework for AI-based misinformation detection. The presentation also discusses both the opportunities and risks associated with the use of large language models (LLMs) in misinformation detection.  

As a case study, the presentation examines propaganda and misinformation surrounding the Russia–Ukraine war. In this context, misleading information is particularly difficult to recognise because it often forms part of coordinated, state-driven information campaigns in which individual pieces of content function as elements of a broader strategic narrative. This case illustrates the complexity of identifying propaganda in contemporary digital communication and the importance of developing context-aware AI approaches.