Аннотации:
Social networks provide a fairly wide range of data that allows one way or
another to evaluate the effect of the dissemination of information. This article
presents the results of a study that describes methods for determining the key
parameters of the model needed to analyze and predict the dissemination of
information in social networks. An approach based on the analysis of
statistical data on user behavior in social networks is proposed. The process
of evaluating the main features of the model is described, including the
mathematical methods used for data analysis and information dissemination
modeling. The study aims to understand the processes of information
dissemination in social networks and develop recommendations for the
effective use of social networks as a communication and brand promotion
tool, as well as to consider the analytical properties of the classical
susceptible-infected-removed (SIR) model and evaluate its applicability to the
problem of information dissemination. The results of the study can be used to
create algorithms and techniques that will effectively manage the process of
information dissemination in social networks.
