Trust, Opinion Diffusion and Radicalization in Social Networks

Abstract

Gossiping models have increasingly been applied to study social network phenomena. This paper is specifically concerned with modeling how the opinions of social agents can be radicalized if the agents interact more strongly with neighbors that share their beliefs. In our model, each agent's belief is represented by a vector of probabilities that a given state is true. The agents average their opinions with that of their neighbors over time, giving more weight to opinions that are closer to their current beliefs. The increasing trust that may exist among like-minded agents is modeled through a weight that is a monotonically decreasing function of the distance in opinion. We consider a continuous (soft) and a discontinuous (hard) model for the weight and analyze the convergence properties.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2011
Accession Number
ADA554891

Entities

People

  • Ananthram Swami
  • Anna Scaglione
  • Lin Li
  • Qing Zhao

Organizations

  • University of California

Tags

DTIC Thesaurus Topics

  • Bayesian Networks
  • Convergence
  • Differential Equations
  • Diffusion
  • Dynamics
  • Engineering
  • Equations
  • Graphs
  • Models
  • Network Topology
  • Numbers
  • Phase Transformations
  • Probability
  • Radicalization
  • Social Networks
  • Societies
  • Transitions

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Operations Research
  • Regression Analysis.