Many researchers focus on how to detect overlapping communities effectively and accurately when coping with large-scale networks in recent years.This paper proposes a novel overlapping community detection algorithm based on a multiple label propagation strategy

called MLPS algorithm.Firstly

MLPS selects a set of nodes as initial seeds by using Influence Maximization Model

each of which is assigned a unique label;Inspired by strategy based on similarity and influence diffusion

MLPS incorporates with these two strategies to guide the process of l

abel propagation;Finally

nodes with the same tag are divided into one community after propagation.Experimental results on synthetic datasets and real networks illustrate that MLPS has both high accuracy and modularity at the same time.In addition

another algorithm named Structural Holes between Communities Detection Algorithm (SHCDA) is presented on the basis of the output of MLPS.SHCDA computes the scores of overlapping nodes who serve as structural holes by analyzing the overlapping structure and position feature of overlapping nodes

and then selects top-

k

structural holes as the output.Experimental results on different datasets show that SHCDA gets the best accuracy.