Multi-dimensional opinion dynamics for social networks with asynchronous updates
Year: 2025
Type: article
Abstract: Multi-dimensional opinion dynamic models can often be used to describe the mutual influence of agents on different topics expressed in social networks. This paper mainly focuses on the multi-dimensional opinion dynamics on social networks with asynchronous updates, where networks include two types of agents: stubborn agents and non-stubborn agents. In the asynchronous update mechanism, the update time instants of each agent are independent and different from those of other agents, which leads to the complexity and time variance of opinion interaction among agents. This paper comprehensively analyzes the convergence of multi-dimensional opinion dynamic models under asynchronous updates, relying on the techniques of binary relation composition and infinite products of sub-stochastic matrices. The results show that the opinions of stubborn agents gradually influence the opinions of non-stubborn agents, and ultimately completely determine the stable opinions of non-stubborn agents. The theoretical results are validated through numerical simulations.
Source: Neurocomputing
Authors: Heng Wang, Panpan Zhu, Lei Shi
Institution: Henan University
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,670
OpenAlex ID: W4413914024