Disclosed is a community detection method for a dynamic residue interaction network, falling within the technical field of computer applications. The method comprises: encoding a residue interaction network into an evolution map, and then screening out rigid residue interaction in the evolution map to obtain a rigid residue interaction network; and performing community detection on the rigid residue interaction network by using a Fast-Newman algorithm, and thereby obtaining a community structure in a dynamic residue interaction network. An evolution map is combined with a Fast-Newman clustering algorithm. The dynamic feature of a residue interaction network is realized by using the evolution map, and therefore, long-lasting interaction in the residue interaction network can be screened out quickly; and a community structure of a protein can be accurately mined by combining the Fast-Newman clustering algorithm, thereby facilitating the development of a follow-up study analyzing the influence on a relationship between the structure and properties of the protein.