  We study a general set of models of social network evolution and dynamics.
The models consist of both a dynamics on the network and evolution of the
network. Links are formed preferentially between 'similar' nodes, where the
similarity is defined by the particular process taking place on the network.
The interplay between the two processes produces phase transitions and
hysteresis, as seen using numerical simulations for three specific processes.
We obtain analytic results using mean field approximations, and for a
particular case we derive an exact solution for the network. In common with
real-world social networks, we find coexistence of high and low connectivity
phases and history dependence.
