A Survey on Algorithmic Interventions in Opinion Dynamics
Abstract
Social media platforms have become critical infrastructures for public communication, where large-scale interaction can both support socially beneficial collective pressure and amplify polarization and conflict. While opinion-dynamics research has long modeled how beliefs evolve through interpersonal influence, the central challenge for healthier online environments increasingly lies in algorithmic interventions: mechanisms that steer collective opinion toward desirable outcomes or dampen harmful dynamics. This survey offers a structured synthesis of this fast-growing, interdisciplinary literature. We organize prior work by the objective optimized -- overall opinion (e.g., consensus or mean opinion), polarization and disagreement, and other quantities -- and review the associated optimization formulations and representative algorithms with mathematical rigor. We also compile intervention-relevant theoretical and empirical findings. Finally, we outline concrete future directions that emerge from this survey.
Cite
@article{arxiv.2603.10756,
title = {A Survey on Algorithmic Interventions in Opinion Dynamics},
author = {Atsushi Miyauchi and Yuko Kuroki and Federico Cinus and Stefan Neumann and Francesco Bonchi},
journal= {arXiv preprint arXiv:2603.10756},
year = {2026}
}