The level of clustering or transitivity in a network can be quantified using triangles, just as the transitivity was quantified for individual nodes in Chapter 5, The Small Scale – Nodes and Centrality. These measures describe, overall, how common triangles are within a network.
The simplest measure of large-scale clustering is transitivity: the fraction of possible triangles that are present. The following example uses the transitivity() function to calculate this value for the example networks:
nx.transitivity(G_karate)
0.2556818181818182
nx.transitivity(G_electric)
0.07190412782956059
nx.transitivity(G_internet)
0.135678391959799
An alternative approach is to average the local clustering coefficient (described in Chapter 5, The Small Scale – Nodes and Centrality) over all nodes. This measure is sometimes called the global clustering coefficient. In...
