For a graph G with N nodes and K edges, the clustering coefficient, C, of the graph G is the average of the clustering coefficient over all nodes [38]:where Di is the number of edges connected to the node i and Ei is the number of edges in the subgraph including the neighbors of node i. The characteristic path length, L, of the graph G is defined as [43]:where dij is the shortest path length between nodes i and j. The normalized clustering coefficient, NC = C/Crand, and the normalized characteristic path length, NL = L/Lrand, were also computed, where Crand and Lrand are, respectively, the mean clustering coefficient and the mean characteristic path length of 1000 matched random networks that preserve the same number of nodes, edges, and degree distribution as the real networks [44]. The small-worldness, SW, of the graph G is computed as the ratio between NC and NL, SW = NC/NL. The network topology may be said to correspond to a “small world” if NC>1 and NL≈1 [38] or if SW>1 [45]. In addition to the
