Abstract: It is of interest to find field-free overlapping communities with low computation complexity in complex networks. We design a local measure known as the "correlation coefficient" to evaluate the density of links by using node optimized duplication and is extended to assess the agglomeration of nodes. In addition, we propose an overlapping community detection algorithm based on node optimized duplication, which uses a cutting strategy to decompose the network and excavate independent or overlapping communities. Experimental results on synthetic and real-world networks show that the proposed method has a higher accuracy and efficiency than several classical algorithms.