An Algorithm for Large-scale Social Network Community Detection and Visualization

The existing community detection algorithms are inefficient and can't satisfy the requirements of graph visualization.Aiming at these problems,two improved heuristic algorithms based on modularity optimization are proposed.This first algorithm uses the method of selecting seed nodes in advance to inhibit the excessive merger of the large community in the Louvain algorithm,and timely merges small communities as well.In addition,since current force-directed algorithms have less obvious community structure and low efficiency,a community layout algorithm for showing large-scale social network community structure is proposed.By using community gravitational force to prompt nodes of the same community together,the second algorithm optimizes community gravity model,and simplifies the algorithm steps too.The experimental results show that the above two algorithms working together can show the massive social network data clearly and effectively.