  We propose a model of network growth that generalizes the deactivation model
previously suggested for complex networks. Several topological features of this
generalized model, such as the degree distribution and clustering coefficient,
have been investigated analytically and by simulations. A scaling behavior of
clustering coefficient $C \sim 1/M$ is theoretically obtained, where $M$ refers
to the number of active nodes in the network. We discuss the relationship
between the recently observed numerical behavior of clustering coefficient in
the coauthor and paper citation networks and our theoretical result. It shows
that both of them are induced by deactivation mechanism. By introducing a
perturbation, the generated network undergoes a transition from large- to
small-world, meanwhile the scaling behavior of $C$ is conserved. It indicates
that $C \sim 1/M$ is a universal scaling behavior induced by deactivation
mechanism.
