Abstract
This study investigates the dynamics of social networks in the context of information confrontation between users. It introduces a simulation method for modeling these conflicts, which is based on game-theoretic and probabilistic approaches. The paper suggests a method for dynamically observing, following, and updating the status of the network. This innovative method conceptualizes information conflicts as a two-player game where the objective is to control as many network nodes as possible. By applying game theory, we formulated a strategy adaptation algorithm that allows each player to modify their decision-making based on the Facebook Researcher open dataset and current network conditions of its Kazakhstani segment. The method for tracking the network’s state dynamically leads to significant reductions in resource use and enhancements in computational efficiency. Comparative computational tests against other methodologies demonstrate the practical value of our approach for addressing a broad spectrum of challenges in information and analytical systems.