Research on the effect of animation IP dissemination based on social network analysis

Abstract

Abstract This paper constructs a GCN-based animation IP propagation algorithm based on social network analysis. Through the analysis of social network influence, a topology-based social network influence model is constructed. Combined with the ranking algorithm, the influence size of animation IP nodes is judged. The LDA model was used to construct a huge document set with the character IPs in the animation as documents. The clustering algorithm is used to classify the propagation effect of animation IP nodes, and the interval of animation IP propagation maximization is found by combining the submodular function maximization. The feature extraction of animation IP propagation effect maximization is performed by graph convolutional neural network. Evaluation indexes are constructed to assess the spreading ability of animation IP under social networks. The results show that the spreading power of animation IP with negative celebrity endorsement is −0.1, and the spreading effect of animation IP with positive communication content is 0.6.