Abstract
Social change occurs when individuals collectively adopt a novel alternative over the status quo in a process known as social diffusion . Aside from works focusing on empirical data and laboratory experiments, agent-based mathematical models have emerged as a valuable framework for studying social diffusion. In particular, dynamical systems theory and control theory have shown great potential to predict long-term behavior and influence the final outcomes of large populations of social individuals. However, a key component that is still not fully developed in classical models is the underlying communication network layer where cyber and physical constraints play a critical role in enabling social exchanges. In other words, to better understand collective human behavior in social diffusion processes, one still needs to further integrate various interaction patterns due to features of cyber information flows and physical communication actions. In this chapter, we present a review of seminal works and recent advances on the mathematical modeling of social diffusion dynamics on complex network systems. First, we present and discuss the key modeling approaches that have been proposed in the literature. Second, we discuss the main advances concerning their analysis in multiplex networks, which capture the complex communication and interaction structures of cyber–physical–human systems (CPHS). Finally, we discuss the recent developments and future works toward controlling such dynamics involving humans-in-multiagent-loops.
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