Abstract
The social world that we observe reflects a web of interdependent processes, with macro‐level structures of organizations, communities, and societies both emerging from and constraining the micro‐level interactions of individuals. Many social phenomena, such as the spread of epidemics, the rise of political insurgency, or the dissolution of organizations, are inherently time varying and depend on interactions between entities within a social system.
Understanding the link between micro‐level interactions and macro‐level dynamics promises to have profound impact on how human societies, organizations, and nations might be structured and how related policy decisions should be made. Toward this end, an increasing number of scientists are using mathematical and computational models to elucidate theoretical problems in social dynamics, often by applying general theories or methods that are well developed in the natural and physical sciences with a view to gaining insight into the underlying generative processes or the dynamic consequences of social relationships. For example, models from statistical physics have been used to study healthcare organizations, population ecology models have been applied to the study of the evolution of industries, and neural networks have been used to model the origins of religious beliefs. Although these new applications have shown promise, their impact has been limited because well‐enforced disciplinary boundaries and conventional scholarly practices constrain the diffusion of ideas and methods across disciplines in the natural and social sciences and engineering.
This meeting was organized to foster intellectual exchange among mathematicians, natural and physical scientists (e.g. biologists, physicists, computer scientists, and engineers), and social and behavioral scientists with a common interest in the development of mathematical and computational methods that can be applied to problems in modeling social dynamics. The meeting served three purposes: (i) to facilitate interdisciplinary conversations among diverse experts and give rise to future collaborative projects of high impact in areas of social dynamics, such as the evolution of social networks, evolutionary and ecological models of social behavior, population dynamics and demography, and organizational dynamics, (ii) to encourage and enable applications of these models to real‐world problems, for example, epidemics, distributed failures due to natural disasters and general consequences of environmental change, and finally (iii) to help NSF identify and nurture emerging research agendas as part of the Human and Social Dynamics priority area by providing a forum for researchers to compare and coordinate lines of research.