Proposing of suggestive influence detection and classification method based on fuzzy logic and feature driven analysis

Abstract

This research proposes an approach to identify and classify tools utilized in information operations that aim to exert suggestive influence. The proposed method combines fuzzy sets theory and fuzzy inference methods with a feature-based analysis approach. By employing this approach, the study focuses on identifying and categorizing tools such propaganda, fake, disinformation, manipulation, and artificial narrative. This framework provides a comprehensive and nuanced understanding of the various tactics employed in information operations, allowing for improved analysis and mitigation strategies.