  Disease, opinions, ideas, gossip, etc. all spread on social networks. How
these networks are connected (the network structure) influences the dynamics of
the spreading processes. By investigating these relationships one gains
understanding both of the spreading itself and the structure and function of
the contact network. In this chapter, we will summarize the recent literature
using simulation of spreading processes on top of empirical contact data. We
will mostly focus on disease simulations on temporal proximity networks --
networks recording who is close to whom, at what time -- but also cover other
types of networks and spreading processes. We analyze 29 empirical networks to
illustrate the methods.
