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Opinion polarization in social networks
Nadia Loy1, Matteo Raviola1, Andrea Tosin1
1Department of Mathematical Sciences 'G. L. Lagrange', Politecnico di Torino, Torino, Italy.
Summary
We developed a kinetic model for opinion dynamics on social networks with varied connectivity. A correlation between initial opinions and individual connections is crucial for observing a polarization switch.
Area of Science:
- Sociophysics
- Statistical Mechanics
- Network Science
Background:
- Opinion formation models often assume regular network structures.
- Understanding opinion dynamics in complex social networks is challenging.
Purpose of the Study:
- To propose a kinetic description for opinion formation on social networks with general connectivity distributions.
- To identify analytical conditions for a polarization switch in opinion dynamics.
Main Methods:
- Developed a Boltzmann-type kinetic model for opinion exchange.
- Analyzed the evolution of mean opinion.
- Validated results using Monte Carlo simulations on social networks.
Main Results:
- Precise analytical conditions for a polarization switch were derived.
- A non-zero correlation between initial opinions and individual connectivity is necessary for a polarization switch.
- Simulations confirmed the analytical findings.
Conclusions:
- The kinetic model provides a framework for studying opinion dynamics in heterogeneous networks.
- Network structure and initial opinion distribution significantly influence opinion polarization.
- This work contributes to understanding collective behavior in social systems.
Keywords:
Boltzmann-type equationsMonte Carlo simulationsSznajd modelinfluencerssociophysicsstatistical network descriptionMore Related Videos
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