Modeling and Simulation of Impact and Control in Social Networks

Abstract

The problems of analysis and prediction in social networks are interpreted for the domain of marketing (other applications are also possible). Algorithms of determination of the strong subgroups and satellites for a network are implemented using the programming language R and tested on model examples. An original algorithm of calculation of the final opinions is proposed, implemented in R and also tested on the model examples. The main idea is that all control efforts in marketing (and other problem domains) should be directed only to the members of strong subgroups because they and only they determine the final opinions of all members of the network. Based on this idea, two problems of the opinions control on networks are studied. First, a static game in normal form where the players maximize the final opinions of all members of a target audience by means of the marketing impact to the initial opinions of some members of the strong subgroups. Second, a dynamic (difference) game in normal form where the players solve the problem of maximization of the sum of opinions of the members of a target audience by means of the closed-loop strategies of impact to the current opinions of the members of strong subgroups. In both cases we received the analytical solutions and conducted their comparative analysis. More complicated versions of the models are studied numerically on the base of the method of qualitatively representative scenarios in computer simulation.