Two complementary representations of a scale-free network

Several studies on real complex networks from different fields as biology, economy, or sociology have shown that the degree of nodes (number of edges connected to each node) follows a scale-free power-law distribution like P(k)≈k-γ, where P(k) denotes the frequency of the nodes that are connected to k other nodes. Here we have carried out a study on scale-free networks, where a line graph transformation (i.e., edges in an initial network are transformed into nodes) is applied on a power-law distribution. Our results indicate that a power-law distribution as P(k)≈k-γ+1 is found for the transformed network together with a peak for low-degree nodes. In the present work, we show a parametrization of this behaviour and discuss its application on real networks as metabolic networks, protein–protein interaction network and World Wide Web.