  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
non degree 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.
