Selective Adaptation of Beliefs and Communication on Cellular Sheaves

TL;DR

This paper extends opinion dynamics on discourse sheaves by introducing directional stubbornness and selective learning, providing a comprehensive framework for understanding belief and communication adaptation with convergence guarantees.

Contribution

It introduces directional stubbornness and selective learning into opinion dynamics on sheaves, along with convergence conditions and bounds on belief and communication adaptation.

Findings

Equilibrium problem becomes a sheaf Poisson equation with forcing.

Gradient flow corresponds to sheaf diffusion on an auxiliary structure.

Bounds quantify when rhetorical accommodation masks belief change.

Abstract

We extend opinion dynamics on discourse sheaves to incorporate "directional stubbornness": agents may hold fixed positions in specified directions of their opinion stalk while remaining flexible in others. This converts the equilibrium problem from harmonic extension to a forced sheaf equation: the free-opinion component satisfies a sheaf Poisson equation with forcing induced by the clamped directions. We develop a parallel theory for "selective learning" of expression policies. When only a designated subset of incidence maps may adapt, the resulting gradient flow is sheaf diffusion on an auxiliary structure sheaf whose global sections correspond to sheaf structures making a fixed opinion profile publicly consistent. For joint evolution of beliefs and expressions, we give conditions (and regularized variants) guaranteeing convergence to nondegenerate equilibria, excluding spurious agreement via vanishing opinions or trivialized communication maps. Finally, we derive stagnation bounds in terms of the rate ratio between opinion updating and structural adaptation, quantifying when rapid rhetorical accommodation masks nearly unchanged beliefs, and conversely when flexible beliefs conform to rigid communication norms.