Convergence, Consensus, and Dissensus in the Weighted-Median Opinion Dynamics

被引:4
作者
Mei, Wenjun [1 ]
Hendrickx, Julien M. [2 ]
Chen, Ge [3 ]
Bullo, Francesco [4 ]
Dorfler, Florian
机构
[1] Peking Univ, Dept Mech & Engn Sci, Beijing 100871, Peoples R China
[2] UC Louvain, Elect & Appl Math, Inst Informat & Commun Technol, B-1348 Louvain La Neuve, Belgium
[3] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100045, Peoples R China
[4] Univ Calif Santa Barbara, Ctr Control Dynam Syst & Computat, Santa Barbara, CA 93106 USA
基金
中国国家自然科学基金;
关键词
Consensus; opinion dynamics; social networks; weighted median; TUTORIAL; NETWORKS;
D O I
10.1109/TAC.2024.3376752
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mechanistic and tractable mathematical models play a key role in understanding how social influence shapes public opinions. Recently, a weighted-median mechanism has been proposed as a new microfoundation of opinion dynamics and validated via experimental data. Numerical studies indicate that this new mechanism recreates some nontrivial real-world features of opinion evolution. In this article, we conduct a thorough analysis of the weighted-median opinion dynamics. We fully characterize the equilibria set, and establish the almost-sure convergence for any initial condition. Moreover, we prove a necessary and sufficient condition for the almost-sure convergence to consensus, as well as a sufficient condition for almost-sure dissensus. We related the rich dynamical behavior of the weighted-median opinion dynamics to two delicate network structures: the cohesive sets and the decisive links. To complement our sufficient conditions for almost-sure dissensus, we further prove that, given the influence network, determining whether the system almost surely achieves persistent dissensus is NP-hard, which reflects that the complexity of the network topology contributes to opinion evolution.
引用
收藏
页码:6700 / 6714
页数:15
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