  In this paper we deal with the structural properties of weighted networks.
Starting from an empirical analysis of a linguistic network, we analyse the
differences between the statistical properties of a real and a shuffled network
and we show that the scale free degree distribution and the scale free weight
distribution are induced by the scale free strength distribution, that is
Zipf's law. We test the result on a scientific collaboration network, that is a
social network, and we define a measure, the vertex selectivity, that can
easily distinguish a real network from a shuffled network. We prove, via an
ad-hoc stochastic growing network with second order correlations, that this
measure can effectively capture the correlations within the topology of the
network.
