Abstract
Empirical studies indicate that communities in real world networks are simultaneously overlapped and hierarchical. This implies that one node can participate in more than one community simultaneously and community further contains sub-communities. However, few methods are capable of simultaneously detecting the overlapping and hierarchical community structure in networks. In this chapter, taking maximal cliques as building blocks of community, a metric is proposed to quantify the overlapping community. With this metric, the overlapping community structure can be efficiently detected by directly finding the optimal partition of network using standard modularity. We also describe the applications on word association network and scientific collaboration network.
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