Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

The importance of a node in social network is identified through set measures called centrality. Degree centrality, closeness betweenness centrality and clustering coefficient are the most frequently used metrics to compute Their computational complexity some cases makes unfeasible, when not practically impossible, their computations. For this reason we focused on two alternative measures, WERW-Kpath Game Thieves, which at same time highly descriptive computationally affordable. Our experiments show that strong correlation exists between Thieves classical measures. This may suggest possibility using them as useful more economic replacements