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
相关论文
共 39 条
[21]  
Hegselmann R, 2002, JASSS-J ARTIF SOC S, V5
[22]  
Hendrickx JM, 2014, IEEE DECIS CONTR P, P2118, DOI 10.1109/CDC.2014.7039711
[23]   ERGODIC THEOREMS FOR WEAKLY INTERACTING INFINITE SYSTEMS AND VOTER MODEL [J].
HOLLEY, RA ;
LIGGETT, TM .
ANNALS OF PROBABILITY, 1975, 3 (04) :643-663
[24]   Byzantine Resilient Distributed Learning in Multirobot Systems [J].
Li, Jiani ;
Abbas, Waseem ;
Shabbir, Mudassir ;
Koutsoukos, Xenofon .
IEEE TRANSACTIONS ON ROBOTICS, 2022, 38 (06) :3550-3563
[25]   Micro-foundation of opinion dynamics: Rich consequences of the weighted-median mechanism [J].
Mei, Wenjun ;
Bullo, Francesco ;
Chen, Ge ;
Hendrickx, Julien M. ;
Doerfler, Florian .
PHYSICAL REVIEW RESEARCH, 2022, 4 (02)
[26]   OPINION DYNAMICS IN HETEROGENEOUS NETWORKS: CONVERGENCE CONJECTURES AND THEOREMS [J].
Mirtabatabaei, Anahita ;
Bullo, Francesco .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2012, 50 (05) :2763-2785
[27]  
Morris R, 2011, PROBAB THEORY REL, V149, P417, DOI 10.1007/s00440-009-0259-x
[28]   Contagion [J].
Morris, S .
REVIEW OF ECONOMIC STUDIES, 2000, 67 (01) :57-78
[29]   A tutorial on modeling and analysis of dynamic social networks. Part II [J].
Proskurnikov, Anton V. ;
Tempo, Roberto .
ANNUAL REVIEWS IN CONTROL, 2018, 45 :166-190
[30]   A tutorial on modeling and analysis of dynamic social networks. Part I [J].
Proskurnikov, Anton V. ;
Tempo, Roberto .
ANNUAL REVIEWS IN CONTROL, 2017, 43 :65-79