  Real growing networks like the WWW or personal connection based networks are
characterized by a high degree of clustering, in addition to the small-world
property and the absence of a characteristic scale. Appropriate modifications
of the (Barabasi-Albert) preferential attachment network growth capture all
these aspects. We present a scaling theory to describe the behavior of the
generalized models and the mean field rate equation for the problem. This is
solved for a specific case with the result C(k) ~ 1/k for the clustering of a
node of degree k. Numerical results agree with such a mean-field exponent which
also reproduces the clustering of many real networks.
