  For most networks, the connection between two nodes is the result of their
mutual affinity and attachment. In this paper, we propose a mutual selection
model to characterize the weighted networks. By introducing a general mechanism
of mutual selection, the model can produce power-law distributions of degree,
weight and strength, as confirmed in many real networks. Moreover, we also
obtained the nontrivial clustering coefficient $C$, degree assortativity
coefficient $r$ and degree-strength correlation, depending on a model parameter
$m$. These results are supported by present empirical evidences. Studying the
degree-dependent average clustering coefficient $C(k)$ and the degree-dependent
average nearest neighbors' degree $k_{nn}(k)$ also provide us with a better
description of the hierarchies and organizational architecture of weighted
networks.
