We generalize the static model by assigning a q-component weight on each vertex. We first choose a component $(mu)$ among the q components at random and a pair of vertices is linked with a color $mu$ according to their weights of the component $(mu)$ as in the static model. A (1-f) fraction of the entire edges is connected following this way. The remaining fraction f is added with (q+1)-th color as in the static model but using the maximum weights among the q components each individual has. This model is motivated by social networks. It exhibits similar topological features to real social networks in that: (i) the degree distribution has a highly skewed form, (ii) the diameter is as small as and (iii) the assortativity coefficient r is as positive and large as those in real social networks with r reaching a maximum around $f approx 0.2$.
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