A physical theory for social behavior

Intercommunity social interactions in organisms from bacteria to humans can drive both mobility and proliferation. Due to the complexity of the individual constituents, construction of continuum models of behavior is difficult. Nevertheless, the existence of collective phenomena such as propagating waves and phase separation suggest that such hydrodynamic theories may be applicable. Here, we combine data-driven techniques with analytical tools from statistical physics to illustrate how to construct continuum models of social behavior. First focusing on socially driven motility, we consider human residential dynamics. Using US Census data, we find that human populations evolve over long length- and time-scales and, with the aid of machine learning, we confirm that the dynamics are local. By modeling humans as utility maximizers, we construct a minimal hydrodynamic theory for interacting human populations and study the effects of "nudging" group preferences on segregation. Finally, we extend our theory to ecological interactions, connecting the effects that utility (or fitness) has on motility as well as birth and death of individuals.