Opinion dynamics in social networks with stubborn agents: An issue-based perspective

被引:79
作者
Tian, Ye [1 ]
Wang, Long [2 ]
机构
[1] Xidian Univ, Sch Mechanoelect Engn, Ctr Complex Syst, Xian 710071, Shaanxi, Peoples R China
[2] Peking Univ, Coll Engn, Ctr Syst & Control, Beijing 100871, Peoples R China
基金
美国国家科学基金会;
关键词
Opinion dynamics; Issue sequences; Path-dependence; Convergence; Confidence bound; TIME MULTIAGENT SYSTEMS; CONSENSUS PROBLEMS; SWITCHING TOPOLOGY; DECISION-MAKING; COORDINATION; EQUILIBRIUM; LEADERSHIP; EVOLUTION; POWER;
D O I
10.1016/j.automatica.2018.06.041
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Classic models on opinion dynamics usually focus on a group of agents forming their opinions interactively over a single issue. Yet generally agreement cannot be achieved over a single issue when agents are not completely open to interpersonal influence. In this paper, opinion formation in social networks with stubborn agents is considered over issue sequences. The social network with stubborn agents is described by the Friedkin-Johnsen (F-J) model where agents are stubborn to their initial opinions. Firstly, we propose a sufficient and necessary condition in terms of network topology for convergence of the F-J model over a single issue. Secondly, opinion formation of the F-J model is investigated over issue sequences. Our analysis establishes connections between the interpersonal influence network and the network describing the relationship of agents' initial opinions for successive issues. Taking advantage of these connections, we derive the sufficient and necessary condition for the F-J model to achieve opinion consensus and form clusters over issue sequences, respectively. Finally, we consider a more general scenario where each agent has bounded confidence in forming its initial opinion. By analyzing the evolution of agents' ultimate opinions for each issue over issue sequences, we prove that the connectivity of the state-dependent network is preserved in this setting. Then the conditions for agents to achieve opinion consensus over issue sequences are established. Simulation examples are provided to illustrate the effectiveness of our theoretical results. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:213 / 223
页数:11
相关论文
共 51 条
[41]   Ergodic Randomized Algorithms and Dynamics Over Networks [J].
Ravazzi, Chiara ;
Frasca, Paolo ;
Tempo, Roberto ;
Ishii, Hideaki .
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2015, 2 (01) :78-87
[42]   Consensus seeking in multiagent systems under dynamically changing interaction topologies [J].
Ren, W ;
Beard, RW .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2005, 50 (05) :655-661
[43]  
Wang L, 2004, LECT NOTES ARTIF INT, V3339, P766
[44]   A new approach to consensus problems in discrete-time multiagent systems with time-delays [J].
Wang Long ;
Xiao Feng .
SCIENCE IN CHINA SERIES F-INFORMATION SCIENCES, 2007, 50 (04) :625-635
[45]   Finite-Time Consensus Problems for Networks of Dynamic Agents [J].
Wang, Long ;
Xiao, Feng .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2010, 55 (04) :950-955
[46]   Controllability of multi-agent systems based on agreement protocols [J].
Wang Long ;
Jiang FangCui ;
Xie GuangMing ;
Ji ZhiJian .
SCIENCE IN CHINA SERIES F-INFORMATION SCIENCES, 2009, 52 (11) :2074-2088
[47]  
Wolfowitz J., 1963, Proceedings of the American Mathematical Society, V14, P733, DOI [10.1090/S0002-9939-1963-0154756-3, DOI 10.1090/S0002-9939-1963-0154756-3, 10.1090/ S0002-9939-1963-0154756-3]
[48]   Asynchronous consensus in continuous-time multi-agent systems with switching topology and time-varying delays [J].
Xiao, Feng ;
Wang, Long .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2008, 53 (08) :1804-1816
[49]   Opinion consensus of modified Hegselmann-Krause models [J].
Yang, Yuecheng ;
Dimarogonas, Dimos V. ;
Hu, Xiaoming .
AUTOMATICA, 2014, 50 (02) :622-627
[50]   Consensus of Hybrid Multi-Agent Systems [J].
Zheng, Yuanshi ;
Ma, Jingying ;
Wang, Long .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (04) :1359-1365