Modeling Social Systems: Transparency, Reproducibility, and Responsibility
Abstract
Mathematical models of complex social systems can enrich social scientific theory, inform interventions, and shape policy. From voting behavior to economic inequality and urban development, such models influence decisions that affect millions of lives. Thus, it is especially important to formulate and present them with transparency, reproducibility, and humility. Modeling in social domains, however, is often uniquely challenging. Unlike in physics or engineering, researchers often lack controlled experiments or abundant, clean data. Observational data is sparse, noisy, partial, and missing in systematic ways. In such an environment, how can we build models that can inform science and decision-making in transparent and responsible ways?
Cite
@article{arxiv.2508.18542,
title = {Modeling Social Systems: Transparency, Reproducibility, and Responsibility},
author = {Maximino Aldana and Roni Barak Ventura and Heather Z. Brooks and Philip S. Chodrow and Filipe Georgiou and Joseph Johnson and Krešimir Josić and Zachary P. Kilpatrick and Kath Landgren and Andrew Nugent and Maurizio Porfiri and Nancy Rodriguez and Pablo Suárez-Serrato and David White and Alexander Wiedemann and Sam Zhang},
journal= {arXiv preprint arXiv:2508.18542},
year = {2025}
}
Comments
5 pages, 1 figure