COMPARATIVE ANALYSIS OF INFORMATION DISTRIBUTION MODELS IN THE INTERNET ENVIRONMENT

Abstract

The study of the process of information dissemination on the Internet is of particular interest today, since this environment in general, and social media in particular, are becoming an increasingly popular channel of communication and, increasingly, the main source of obtaining information, so they can contribute to the spread of fake news, hatred and misinformation. This can have serious consequences for society, undermining trust and fueling conflicts. Social networks are becoming a powerful tool for manipulating public opinion. Propaganda of the aggressor country actively uses them to spread fake news, which undermines trust in official sources of information and disorients society. The speed of information dissemination in the Internet environment allows creating an "avalanche" effect, when fake news spreads at an incredible speed, which makes it difficult to refute them. Modeling the spread of information in the Internet environment allows you to understand its impact on people's behavior in the economic, political and social spheres. The article provides a comparative analysis of various information dissemination methods, including noise and impact models, viral propagation models, dependent propagation models, rumor propagation models, influencer models, and models based on cellular automata, including principles, features, and possible limitations. This analysis is aimed at determining the effectiveness of each model in reproducing real processes of information dissemination, as well as at identifying the possibility of their application in various scenarios. The characteristics are summarized and limitations on the application of these models for the study of information dissemination on the Internet are defined.