Zhejiang Gongshang University
This paper aims to find the optimal node to control the public opinion information in the social network, and define the public opinion control criteria of the social network in combination with the centrality of the user group, so as to identify the key nodes of the dissemination of public opinion information in the social network. In addition, this paper also proposes a cooperative game income allocation method based on user groups, using Shapley value distribution of different user groups of users through the mutual positions of power and function of surplus, to identify the key node is marked as separators (SVID) based on the Shapley value of information, and puts forward an adaptive efficient SVIDA algorithm. Finally, SIR model and real network data sets are combined to carry out numerical simulation and algorithm comparison to verify the effectiveness of the proposed method. The experimental results show that the SVIDA method proposed in this paper can control public opinion in homogeneous, heterogeneous and real social network environment at home and abroad, and its efficiency is greatly improved compared with other public opinion control algorithms. According to the SIR model simulation results, when the proportion of delimiter q is increased, the proportion of infected nodes decreases faster, and the proportion of immune nodes increases faster. In the network environment with faster transmission speed, the public opinion control advantages of SVIDA method proposed in this paper are more obvious.