A dynamic model, often used by physicists and biologists, begins as a small network or even a single node.
The modeler then uses a (usually randomized) rule on how newly arrived nodes form links in order to increase the size of the network.
The method tests the hypothesis that, given some initial setting and parameter values, a certain network structure will emerge as an equilibrium of this game.
[1] These models were further developed by Jackson and Watts, who put this approach to a dynamic setting to see how the network structure evolve over time.
[3] With this general framework, modelers can reproduce almost every stylized trait of real-life networks.