  Adaptive social networks, in which nodes and network structure co-evolve, are
often described using a mean-field system of equations for the density of node
and link types. These equations constitute an open system due to dependence on
higher order topological structures. We propose a new approach to moment
closure based on the analytical description of the system in an asymptotic
regime. We apply the proposed approach to two examples of adaptive networks:
recruitment to a cause model and adaptive epidemic model. We show a good
agreement between the improved mean-field prediction and simulations of the
full network system.
