Discrete-Time Polar Opinion Dynamics with Heterogeneous Individuals

Ji Liu, Mengbin Ye, Brian D.O. Anderson, Tamer Basar, Angelia Nedic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


This paper considers a discrete-time opinion dynamics model in which each individual's susceptibility to being influenced by others is dependent on her current opinion. We first propose a general opinion dynamics model based on the DeGroot model, with a general function to describe the functional dependence of each individual's susceptibility to her own opinion, and characterize the set of all equilibria and stability of nontrivial equilibria. We then consider two classes of functions in which the individual's susceptibility depends on the polarity of her opinion (i.e., how extreme her opinion is), and provide motivating social examples. First, we consider stubborn positives, who have reduced susceptibility if their opinions are at one end of the interval and increased susceptibility if their opinions are at the opposite end. Second, we consider stubborn extremists, who are less susceptible when they hold opinions at either end of the opinion interval. For each susceptibility model, we establish limiting behavior for different initial conditions. Networks consisting of individuals with both types of susceptibility functions are also considered.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538613955
StatePublished - Jul 2 2018
Externally publishedYes
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: Dec 17 2018Dec 19 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370


Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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