Modeling of manipulative informational influence in social networks

Manipulative models of information influences in social networks are considered. Their descriptions in the system dynamics notation in the form of a flowchart and the corresponding system of differential equations are given. Model experiments with the application of advanced simulation platform Anylogic was carried out. Comparing agent-based and system-dynamic models showed high agreement with each other and with statistical data. Based on the cluster analysis using real statistical data was allocated typological groups in the sample villages of Russia, which differ in the average time spreading of information influences. System-dynamic models of information influences spreading in social networks have been successfully tested. In addition, the Gibbs's postulate on statistical ensembles with respect to spreading of an idea in student's environment was confirmed. The high consistency of simulation results with empirical data is shown (the coefficients of determination are not less than 90%). Models allow the forecasting of informational influences and informational counteractions, and to study various scenarios of their development.