Communities (also called modules) within networks are groups of nodes that are richly connected to one another within the larger framework of the entire network. Communities have been detected in many complex networks, and tend to group nodes with similar features or functions, simplifying and illuminating the structure of the network (for review, see Fortunato, 2010 (Fortunato, 2010)). Community detection has been the subject of intense interest since 2004, when Newman & Girvan proposed the “modularity” measure, which quantifies the “quality” or amount of community structure found in a network (Newman and Girvan, 2004). For a given partition of a graph into modules, the modularity of the graph is the difference between the number of edges found within modules and the number of edges predicted to lie within modules if all edges in the network were distributed randomly (Newman and Girvan, 2004). Algorithms that optimize this measure have been widely used to detect communities in networks, though several alternatives exist (see Fortunato, 2010).
