To solve the problem of graph data distributed processing, graph partitioning is more and more important. This paper studies the method of partitioning a large-scale dynamic graph. According to the characteristics of graph structure and dynamic graph, a dynamic graph partitioning algorithm based on neighborhood is proposed and implemented. The algorithm consists of two stages, static partition and dynamic adjustment. A static graph partitioning combines the cut-edges and the existing partition tools to get an optimized method. The dynamic adjustment focuses on the transferring of vertexes to its neighborhood. It calculates the value of vertexes transferring load and optimize the operations. Experiments on a series of common graph datasets show significant effect on the indexes of balance and cut-edges, which means the partition is reasonable and balanced.