Since the semantic social network (SSN) is a new kind of complex networks, the traditional community detection algorithms which require presetting the number of the communities, cannot detect the overlapping communities. To solve this problem, an overlapping community structure detecting algorithm in semantic social networks based on the link-block is proposed. First, the measurement of the semantic weight of links for the link-block is established depending on the analysis of LBT. Secondly, a method to measure the semantic links weight of link-block area is developed to provide the measurement of semantic information. Thirdly, the overlapping community detection cluster method is designed, based on the semantic weight of links, with the link-block as the element. Finally, the SQ modularity for the measurement of semantic communities is obtained. The efficiency and feasibility of the algorithm and the semantic modularity are verified by experimental analysis.