Progressive Information Polarization in a Complex-Network Entropic Social Dynamics Model
Authored by Chao Wang, Jin Ming Koh, Kang Hao Cheong, Neng-Gang Xie
Date Published: 2019
DOI: 10.1109/access.2019.2902400
Sponsors:
Chinese National Natural Science Foundation
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
The advent of social media and technologies augmenting social
communication has dramatically amplified the role of rumor spreading in
shaping society, via means of misinformation and fact distortion.
Existing research commonly utilize contagion mechanisms, statistical
mechanics frameworks, or complex-network opinion dynamics models. In
this paper, we incorporate information distortion and polarization
effects into an opinion dynamics model based on information entropy,
modeling imprecision in human memory and communication, and the
consequent progressive drift of information toward subjective extremes.
Simulation results predict a wide variety of possible system behavior,
heavily dependent on the relative trust placed on individuals of
differing social connectivity. Mass-polarization toward a positive or
negative consensus occurs when a synergistic mechanism between
preferential trust and polarization tendencies is sustained; a division
of the population into segregated groups of different polarity is also
possible under certain conditions. These results may aid in the analysis
and prediction of opinion polarization phenomena on social platforms,
and the presented agent-based modeling approach may aid in the
simulation of complex-network information systems.
Tags
Complex networks
Social dynamics
Internet
information theory
Game
Length
Behavioral sciences
Information
propagation
Information polarization
Communicative distortion
Agent
interaction
Rumors