ON A HYBRID METHOD FOR MODELING INFORMATION DISSEMINATION PROCESSES BASED ON AUTOMATA AND DIFFUSION MODELS

Abstract

Context. The modern information society, with its rapidly expanding means of information exchange and globalized data, offers the opportunity to study information dissemination, investigate its impact, and create information security systems. Mathematical modeling methods are widely used in the development of information dissemination systems and technologies. Thermal, diffusion, and mechanical processes – that is, processes occurring in a continuous medium – are considered fundamental. Among the various modeling approaches, equations of mathematical physics, which formalize the fundamental laws of substance transfer, are often used.
Objective. The aim of this paper is to develop a comprehensive, formalized approach to numerically modeling the dynamics of information dissemination processes in social networks based on the principles of cellular automata and diffusion models. The subject of the study is the analysis of the dynamics of the level of information generated based on the internal behavior of each network cell, assuming that its initial state is formed as a result of the influence of certain processes outside the information communities.
Method. This paper proposes a hybrid approach to modeling information dissemination processes based on cellular automata, which observes the internal and external dynamics of individual cells. The state change of the automata model is described by a specified transition function and rules for generating output signals, while a diffusion approach based on heat conduction principles is used to formalize internal changes in the cell’s state. Computational experiments were conducted to model the dynamics of information dissemination processes, taking into account various types of external influences from others, and calculations of information dissemination dynamics indicators in social network communities are presented.
Results. The proposed hybrid model allows us to describe and analyze information dissemination processes within a social group, which is formed, for example, from social network subscribers. The group is divided into subgroups that are relatively homogeneous in terms of specific indicators in the form of online communities.
Information processes were modeled taking into account various external influences from surrounding environments (using von Neumann and Moore neighborhoods as examples) with explicitly defined transition and exit functions. Internal information dissemination processes in specific cells were formalized using scalar heat equations. Numerical calculations of information dissemination dynamics in each community and the group as a whole were obtained, and a solution to information content problems (participants’ attitudes toward a specific problem) in subgroups was proposed based on determining the locations of centers of iinfluence.
Conclusions. This article examines the application of cellular automata principles to modeling the dynamics of information dissemination processes. A new approach is proposed that, in addition to the automata model, considers the internal behavior of each cell, assuming that its initial state is formed as a result of certain intracellular processes at each time interval. In other words, a hybrid version of a cellular automaton for observing the internal and external dynamics of individual cells is considered, whereby the change in the states of the automaton model is described by a given transition function with certain rules for generating output signals, and a “mechanistic” approach based on the principles of thermal conductivity is used to formalize internal changes in the state of the cell.