Sociohydrodynamics: Data-driven modeling of social behavior

• 成果类型: Article
• 署名作者: Seara, Daniel S.; Colen, Jonathan; Fruchart, Michel; Avni, Yael; Martin, David G.; Vitelli, Vincenzo
• 署名单位: University of Chicago; University of Chicago; Old Dominion University; Centre National de la Recherche Scientifique (CNRS); Universite PSL; Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI); University of Chicago; University of Chicago
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-12175
• DOI: 10.1073/pnas.2508692122
• 发表日期: 2025-08-29
• 关键词: residential segregation; ethnic-preferences; dynamic-models; chemotaxis; promotes; biodiversity; persistence; EQUATIONS; EVOLUTION; strategy

摘要

Living systems display complex behaviors driven by physical forces as well as decisionof socially generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data are available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard hydrodynamic assumptions to construct a sociohydrodynamic model. Solving our minimal hydrodynamic model, calibrated using statistical inference, qualitatively captures key features of residential dynamics at the level of individual US counties. We highlight that a social memory, akin to hysteresis in magnets, emerges in the segregation-integration transition even with memory-less agents. While residential segregation is a multifactorial phenomenon, this physics analogy suggests a simple mechanistic explanation for the phenomenon of neighborhood tipping, whereby a small change in a neighborhood's population leads to a rapid demographic shift. Beyond residential segregation, our work paves the way for systematic investigations of decision-guided motility in real space, from micro-organisms to humans, as well as fitness-mediated motion in more abstract spaces.