Abstract: LDAG( DAG algorithm based on linear threshold) algorithm is a heuristic algorithm for maximizing the influence of social networks． It has the characteristics of high accuracy and high efficiency． When solving the problem of maximizing the influence of social networks，the network influence propagation model is given priority，and then the topological structure of social networks is ignored． In this paper，the LDAG algorithm is improved by using the structure of social network community to select the key nodes of influence propagation．The key nodes are used to simplify the construction process of directed acyclic graph，optimize the time complexity and space complexity of the algorithm，and validate the rationality of the algorithm by using two effective experimental data sets．

Key words: social network, key nodes, LDAG algorithm