 How should we expect beliefs and opinions to change within a social group? How might they rationally change? The computational approach to these kinds of questions attempts to understand basic dynamics of the target phenomenon by building, running, and analyzing simulations. Simulations may start with a model of interactive dynamics and initial conditions, which might include, for example, the initial beliefs of individual agents and how prone those agents are to share information and listen to others. The computer calculates successive states of the model (“steps”) as a function (typically stochastic) of preceding stages. Researchers collect and analyze simulation outputs, which might include, for example, the distribution of beliefs in the simulated society after a certain number of rounds of communication. Because simulations typically involve many stochastic elements (which agents talk with which agents at what point in the simulation, what specific beliefs specific agents start with, etc.), data is usually collected and analyzed across a large number of simulation runs.