To solve the problem of overlapping community detection in complex networks, many types of methods have been proposed, and Symmetric Binary Nonnegative Matrix Factorization (SBNMF) based overlapping community detection method is one of the most representative methods. However, SBNMF performs poorly when dealing with complex networks with sparse links within communities. In view of this, an Improved SBNMF (ISBNMF) based overlapping community detection method was proposed. Firstly, the factor matrix obtained by the symmetric nonnegative matrix factorization was used to construct a new network with dense links within communities. Then, the SBNMF model based on Frobenius norm was used to factorize the adjacency matrix of the new network. Finally, a binary matrix that can explicitly indicate the community membership of nodes was obtained by means of grid search method or gradient descent method. Extensive experiments were conducted on synthetic and real network datasets. The results show that ISBNMF performs better than SBNMF and other representative methods.