Misinformation Dynamics in Social Networks

TL;DR

This paper introduces a continuous-fidelity field theory for social networks, revealing universal mechanisms affecting information quality and providing strategies to improve fidelity in large-scale communication systems.

Contribution

It develops a novel analytical framework for understanding misinformation dynamics across multiplex social networks, identifying key mechanisms influencing information fidelity.

Findings

Groupthink blending drives fidelity to initial group mean.

Cross-community flow causes irreversible information dilution.

Connectivity can reduce information integrity, suggesting control strategies.

Abstract

Information transmitted across modern communication platforms is degraded not only by intentional manipulation (disinformation) but also by intrinsic cognitive decay and topology-dependent social averaging (misinformation). We develop a continuous-fidelity field theory on multiplex networks with distinct layers representing private chats, group interactions, and broadcast channels. Our analytic solutions reveal three universal mechanisms controlling information quality: (i) groupthink blending, where dense group coupling drives fidelity to the initial group mean; (ii) bridge-node bottlenecks, where cross-community flow produces irreversible dilution; and (iii) a network-wide fidelity landscape set by a competition between broadcast truth-injection and structural degradation pathways. These results demonstrate that connectivity can reduce information integrity and establish quantitative control strategies to enhance fidelity in large-scale communication systems.