Assessing the impact of promotion algorithms in social networks on user popularity

Abstract

In the modern world, social networks are one of the main tools for interaction between people and are becoming more and more popular. Therefore, it is important to understand how the algorithms of social networks and the structural and dynamic aspects of user behavior affect their popularity. The study is based on graph theory and the Frobenius – Perron theory of non-negative matrix decomposition using the stationary distribution of Markov chains. As a result, the behavior of the model over a long period of time is shown and appropriate conclusions are made about the distribution and popularity of users in social networks.