Assessment of the main features of the model of dissemination of information in social networks

Imanberdi A. Lira L. Aitolkyn K. Leila R. Abitova G. Aigerim B. Ainur O. Assem B.
December 2023 Institute of Advanced Engineering and Science

International Journal of Electrical and Computer Engineering
2023 #13 Issue 6 6729 - 6736 pp.

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.

Cluster analysis , Information dissemination , model , Model parameters , Social networks , Susceptible-infected-removed

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Department of Information Systems, Faculty of Information Technology, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Intelligent Systems and Cybersecurity, Astana IT University, Astana, Kazakhstan
Department of Biostatistics, Bioinformatics and Information Technologies, Astana Medical University, Astana, Kazakhstan

Department of Information Systems
Department of Intelligent Systems and Cybersecurity
Department of Biostatistics

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