Those who study creativity, especially from a computational perspective, have long understood the role of social influence in the creative process. This has motivated many efforts to simulate social mechanics in artificial creative systems. However, these simulations have often replicated generic or assumed human behaviors rather than specific anthropological data. In this work we take a more focused approach by quantitatively measuring interactions between creators in online social communities and replicating observed phenomena in a simulated environment. The primary contributions of this thesis are 1) defining quantitative metrics for comparing human and simulated social networks of creators, 2) providing social interaction data and analysis for several online creative societies including Skratch, FanFiction, and r/ArtCrit, 3) defining AMACS, a flexible Architecture for Multi-Agent Creative Societies, and 4) demonstrating how manipulation of AMACS hyperparameters can induce a broad range desired behaviors, including behavior observed in human communities. This thesis will enable those who manage and participate in human creative societies, including administrators of large online communities of creators, to better understand the behavior of their community members. It will also help those seeking to simulate interactions between creative agents to identify differences between their simulations and human communities, providing points of inspiration and correction that may improve simulation efficacy.