English

Data-Driven Modeling of U.S. Ideological Dynamics

Physics and Society 2025-10-15 v1 Dynamical Systems

Abstract

The dynamics of political opinion are a critical component of modern society with large-scale implications for the evolution of intra- and international political discourse and policy. Here we utilize recent high-resolution survey data to quantitatively capture leading-order psychological and information-environmental patterns. We then inform simulations of a theoretical dynamical framework with several different models for how populations' ideology evolves over time, including a model which reproduces current macro-scale ideological distributions given the empirical micro-scale data gathered. This effort represents an attempt to discover true underlying trends of political reasoning in general audiences, and to extrapolate the long-term implications of those trends as they interact with the political exposure landscape. Accurate modeling of this ecosystem has the potential to predict catastrophic outcomes such as hyperpolarization, and to inform effective intervention strategies aimed at preserving and rebuilding constructive political communication.

Keywords

Cite

@article{arxiv.2510.11983,
  title  = {Data-Driven Modeling of U.S. Ideological Dynamics},
  author = {David Sabin-Miller and Christopher Harding},
  journal= {arXiv preprint arXiv:2510.11983},
  year   = {2025}
}

Comments

14 pages, 12 figures

R2 v1 2026-07-01T06:35:06.353Z