Social network is one of the most important true-life networks in our real world scenarios. A typical feature of the social network is the dense sub-structure (quasi-clique or community) which is essential for understanding the network's internal structure and function. Traditional social network analysis usually focuses on the centrality and power of a single individual or entity, however, in people's daily life, a group or an organization often holds a more influential position and plays a more important role. Therefore, in this paper, we first present a parallel algorithm for the detection of quasi-cliques, and then we describe the techniques that are useful for evaluating the centrality and significance of a quasi-clique. Computational results on a real call graph from a telecom career and a collaboration network of co-authors are given in the end.