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Most real-world networks are weighted graphs with the weight of the edgesreflecting the relative importance of the connections. In this work, we studynon degree dependent correlations between edge weights, generalizing thus thecorrelations beyond the degree dependent case. We propose a simple method tointroduce weight-weight correlations in topologically uncorrelated graphs. Thisallows us to test different measures to discriminate between the differentcorrelation types and to quantify their intensity. We also discuss here theeffect of weight correlations on the transport properties of the networks,showing that positive correlations dramatically improve transport. Finally, wegive two examples of real-world networks (social and transport graphs) in whichweight-weight correlations are present.Comment: 8 pages, 8 figure

Transport on weighted networks: When the correlations are independent of the degree