Most real-world networks are weighted graphs with the weight of the edges reflecting the relative importance of the connections. In this work, we study nondegree dependent correlations between edge weights, generalizing thus the correlations beyond the degree dependent case. We propose a simple method to introduce weight-weight correlations in topologically uncorrelated graphs. This allows us to test different measures to discriminate between the different correlation types and to quantify their intensity. We also discuss here the effect of weight correlations on the transport properties of the networks, showing that positive correlations dramatically improve transport. Finally, we give two examples of real-world networks (social and transport graphs) in which weight-weight correlations are present.

• Received 13 April 2007

DOI:https://doi.org/10.1103/PhysRevE.76.066106