Improved SLPA algorithm based on the Louvain community module optimization capability

In today's information age, with the rapid development of computer technology, the urban intelligence based on Web2.0 environment has gradually become the current social research hotspot.In such a context, stricter and more comprehensive requirements for system design: efficiency, convenience, flexibility, flexibility, scalability and acceptable performance; From the perspective of social network analysis, the core problem in various social networks is to discover the relationship between users and users. In these methods, a good solution is found: to realize the system function through the relationships and connections between users. This scheme is a "user" -centric idea.After making full use of Louvain partitioning, constructing node importance calculation method, using node importance analysis label propagation ability in label propagation algorithm, and developing new label update strategies through node importance sorting and label propagation ability, the final community division results has obtained. Experimental results on both artificial and real networks show that the proposed algorithm has high accuracy and stability.