Recently, community detection in social networks is studied as a major problem. Most existing methods solve the problem of community detection using link structure of networks. In this case, communities only reflect the topological features of network. Documents of social members in network are ignored. In this paper, hierarchical modularity maximization algorithm that is frequently used in literature is modified using similarities between members. Experiments on real data sets, proposed algorithm can achieve a better performance.