The invention provides an influence maximization algorithm based on a community structure and applicable to a paper cooperation network. The influence maximization algorithm comprises the following steps of:1) in a community discovering phase, a, constructing the paper cooperation network, b, merging local communities, c, constructing a new network image, and d, ending; and 2) in a seed node selecting phase, a, calculating the influence of each community, b, selecting the corresponding nodes in the community largest in influence, and c, ending. According to the invention, a new solution scheme is provided for the influence maximization problem of the paper cooperation network, and indicated by results, for the ICM model, the COMAX algorithm provided by the invention is close to a greedy algorithm in influence coverage range, and the time efficiency is very good.