Nonlinear Opinion Dynamics with Tunable Sensitivity
Abstract
We propose a continuous-time multi-option nonlinear generalization of classical linear weighted-average opinion dynamics. Nonlinearity is introduced by saturating opinion exchanges, and this is enough to enable a significantly greater range of opinion-forming behaviors with our model as compared to existing linear and nonlinear models. For a group of agents that communicate opinions over a network, these behaviors include multistable agreement and disagreement, tunable sensitivity to input, robustness to disturbance, flexible transition between patterns of opinions, and opinion cascades. We derive network-dependent tuning rules to robustly control the system behavior and we design state-feedback dynamics for the model parameters to make the behavior adaptive to changing external conditions.} The model provides new means for systematic study of dynamics on natural and engineered networks, from information spread and political polarization to collective decision making and dynamic task allocation.
Cite
@article{arxiv.2009.04332,
title = {Nonlinear Opinion Dynamics with Tunable Sensitivity},
author = {Anastasia Bizyaeva and Alessio Franci and Naomi Ehrich Leonard},
journal= {arXiv preprint arXiv:2009.04332},
year = {2023}
}