Most traditional community detection algorithms always consider single factor. Friends who have close relationship may have different concerns and users who have common concerns may not be in a circle of friends. To solve the problems, this thesis presents a hybrid community detection algorithm HCDA, which takes into account the concerns of the community network nodes, but also consider the topological structure of community network. On this basis, it expands iteratively the community by the community gain value between adjacent nodes to find the real interest groups among friend circles. The experimental results illustrate that compared with other methods the proposed algorithm can find the community more accurately.