Graph-Theoretical Model of the Information-Psychological "Mental War"

Abstract

The objective of this work is to develop a model of "mental wars." Generative artificial intelligence is employed to modernize the basic hierarchical model. The proposed methodology involves expanding the model with new concepts, categories, and connections between them, generated through artificial intelligence systems and large language models. By applying clustering based on modularity classes and node ranking within the "mental wars" network model, the authors enhance and extend the basic hierarchical model, uncover new aspects, and deepen the understanding of the content, objectives, and consequences of information-psychological mental wars.

Keywords: mental wars, hierarchical model, generative artificial intelligence, large language models, semantic network, clustering, modularity