Empirical analysis and modelling social network user interaction behavior and time characteristics based on selection preference

Abstract

User interaction plays an important role in the formation of network public opinion. Many studies have found the power-law characteristics and multimode characteristics of individual complex behavior in social network, but it is difficult to systematically describe and explain the physical phenomena of individual interaction by mathematical methods. To deeply analyze the causes of this phenomenon, it is inseparable from the detailed study of micro individuals and their interaction process. In social network, the reposting behavior of a specific user reflects his individual preference regarding the process of interaction. The frequency of interaction between friends with high preference is much higher than that of friends with low preference. For the first time, we try to study the interaction behavior of users from the perspective of micro individuals by considering user selection preferences. We establish a mathematical expression model of user interaction behavior in social network. The model give the mathematical description dual-mode characteristics of the physical phenomenon of bimodal characteristics. Through the theoretical analysis and simulation experiments of the model, we analyze the distribution of user interaction behavior and the time characteristics of user interaction process. The empirical analysis of data gathered from Weibo also confirms the conclusion of theoretical research.