This paper proposes a community key node shortest path algorithm based on random node social network. The algorithm divides the social network into communities and determines the shortest paths between core nodes and non-core nodes in each community. Facing the complex information and cultural environment and the influence of foreign cultures, it is necessary to use its media to integrate the advantages of new technologies and platforms, and to innovate the propagation paths and platforms of traditional culture. The path of mutual integration is expected to provide reference for the inheritance and promotion of China's excellent traditional culture and the enrichment of ideological and political education resources for college students. The hypothesis processing of the model is carried out, the dynamic performance evaluation model is established, and finally the dynamic performance modeling based on python is established.