Abstract: Community detection has been a research topic in the complex network area. The global information of the whole network, which is required by the traditional community detection algorithms, is hard to get when the scale of the network grows. The study presents a novel algorithm for detecting local community structure based on hybrid centrality. After identifying the network nodes with hybrid centrality, our algorithm can detect local community structure starting from some important nodes. In addition, to better understand the algorithm, a subsequent processing is continued. The present algorithm is applied to some simple examples, including computer-generated and real-world networks. And the experimental results are analyzed by comparing with other traditional algorithms.