This chapter has shown us how simulations can be used to better understand both the processes that create network structure and the processes that are influenced by network structure. The Watts-Strogatz model creates small-world networks by adding random shortcuts to a highly-clustered ring network. Preferential attachment creates heavy-tailed, scale-free networks, where a few nodes have most of the connections. Configuration models are used to construct synthetic networks with properties similar to real networks. Finally, this chapter showed how agent-based modeling can be used to simulate a social learning process occurring on an existing network structure. In the next chapter, you'll learn about working with data that represents objects in space or time.
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