Stochastic Opinion Dynamics under Social Pressure in Arbitrary Networks

Fuente: arXiv
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Autori principali: Tang, Jennifer, Adler, Aviv, Ajorlou, Amir, Jadbabaie, Ali
Natura: Preprint
Pubblicazione: 2023
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author Tang, Jennifer
Adler, Aviv
Ajorlou, Amir
Jadbabaie, Ali
author_facet Tang, Jennifer
Adler, Aviv
Ajorlou, Amir
Jadbabaie, Ali
contents Social pressure is a key factor affecting the evolution of opinions on networks in many types of settings, pushing people to conform to their neighbors' opinions. To study this, the interacting Polya urn model was introduced by Jadbabaie et al., in which each agent has two kinds of opinion: inherent beliefs, which are hidden from the other agents and fixed; and declared opinions, which are randomly sampled at each step from a distribution which depends on the agent's inherent belief and her neighbors' past declared opinions (the social pressure component), and which is then communicated to her neighbors. Each agent also has a bias parameter denoting her level of resistance to social pressure. At every step, each agent updates her declared opinion (simultaneously with all other agents) according to her neighbors' aggregate past declared opinions, her inherent belief, and her bias parameter. We study the asymptotic behavior of this opinion dynamics model and show that the agents' declaration probabilities approaches a set of equilibrium points of the expected dynamics using Lyapunov theory and stochastic approximation techniques. We also derive necessary and sufficient conditions for the agents to approach consensus on their declared opinions. Our work provides further insight into the difficulty of inferring the inherent beliefs of agents when they are under social pressure.
format Preprint
id arxiv_https___arxiv_org_abs_2308_09275
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Stochastic Opinion Dynamics under Social Pressure in Arbitrary Networks
Tang, Jennifer
Adler, Aviv
Ajorlou, Amir
Jadbabaie, Ali
Systems and Control
Social and Information Networks
Dynamical Systems
Optimization and Control
Social pressure is a key factor affecting the evolution of opinions on networks in many types of settings, pushing people to conform to their neighbors' opinions. To study this, the interacting Polya urn model was introduced by Jadbabaie et al., in which each agent has two kinds of opinion: inherent beliefs, which are hidden from the other agents and fixed; and declared opinions, which are randomly sampled at each step from a distribution which depends on the agent's inherent belief and her neighbors' past declared opinions (the social pressure component), and which is then communicated to her neighbors. Each agent also has a bias parameter denoting her level of resistance to social pressure. At every step, each agent updates her declared opinion (simultaneously with all other agents) according to her neighbors' aggregate past declared opinions, her inherent belief, and her bias parameter. We study the asymptotic behavior of this opinion dynamics model and show that the agents' declaration probabilities approaches a set of equilibrium points of the expected dynamics using Lyapunov theory and stochastic approximation techniques. We also derive necessary and sufficient conditions for the agents to approach consensus on their declared opinions. Our work provides further insight into the difficulty of inferring the inherent beliefs of agents when they are under social pressure.
title Stochastic Opinion Dynamics under Social Pressure in Arbitrary Networks
topic Systems and Control
Social and Information Networks
Dynamical Systems
Optimization and Control
url https://arxiv.org/abs/2308.09275