This chapter presents the Siena simulation modeling framework, based on the stochastic actor-oriented model, and its use in analyzing dynamic social network evolution. Siena not only examines how networks evolve but also how behavioral attributes and network structures change together. Unlike traditional graph theory-based tools that focus on static networks, Siena’s longitudinal analysis offers insights into network dynamics. The use of machine learning and simulation to study these dynamics is increasingly popular among researchers. Studying the formation and evolution of interactive networks with Siena is valuable for understanding networks in communities, organizations, and enterprises. Investigating changes in network structures, such as reciprocity and triadic closure, across different evolutionary stages is also important.