Signed Social Networks With Biased Assimilation

• 成果类型: Article
• 署名作者: Wang, Lingfei; Hong, Yiguang; Shi, Guodong; Altafini, Claudio
• 署名单位: Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Tongji University; University of Sydney; Linkoping University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3121221
• 发表日期: 2022
• 页码: 5134-5149
• 关键词: Social networking (online); bifurcation; Analytical models; Network topology; stability analysis; Hypercubes; TOPOLOGY; biased assimilation; opinion dynamics; signed social networks

摘要

A biased assimilation model of opinion dynamics is a nonlinear model, in which opinions exchanged in a social network are multiplied by a state-dependent term having the bias as exponent and expressing the bias of the agents toward their own opinions. The aim of this article is to extend the bias assimilation model to signed social networks. We show that while for structurally balanced networks, polarization to an extreme value of the opinion domain (the unit hypercube) always occurs regardless of the value of the bias, for structurally unbalanced networks, a stable state of indecision (corresponding to the centroid of the opinion domain) also appears, at least for small values of the bias. When the bias grows and passes a critical threshold, which depends on the amount of disorder encoded in the signed graph, then a bifurcation occurs and opinions become again polarized.