Discord in the voter model for complex networks.
Antoine Vendeville1, Shi Zhou1, Benjamin Guedj1,2
1Department of Computer Science, University College London, WC1V 6LJ London, United Kingdom.
Physical Review. E
|March 16, 2024
Summary
We developed a method to calculate discord probability in social networks, offering insights into how hostility and polarization evolve. This analysis helps understand online community dynamics and communication patterns.
Area of Science:
- Computational Social Science
- Network Science
- Mathematical Modeling
Background:
- Online social networks are central to communication but foster undesirable effects like hostility and polarization.
- Analytical tools are needed to understand the dynamics of these complex social systems.
- Discord, hostility, and echo chambers are key phenomena requiring quantitative study.
Purpose of the Study:
- To introduce a novel method for calculating the probability of discord between agents in social networks.
- To analyze the evolution of discord in the multistate voter model, with and without zealots.
- To provide a generalizable framework applicable to diverse network structures and opinion dynamics.
Main Methods:
- Formal introduction of a method to compute discord probability in multistate voter models.
- Application to any directed, weighted graph with finite opinions and varied agent update rates.
- Development of a linear system of ordinary differential equations to describe discord evolution.
- Proof of a unique equilibrium solution computable via an iterative algorithm.
Main Results:
- A generalized definition of active links density accounting for long-range, weighted interactions.
- Demonstration of findings on real-life and synthetic networks.
- Investigation into the impact of network clustering on discord.
- Uncovering varied behaviors in polarized networks and between antagonistic communities.
Conclusions:
- The proposed method offers a precise, non-approximated way to quantify discord in social networks.
- Understanding discord evolution is crucial for mitigating negative online social phenomena.
- Network topology, particularly clustering, significantly influences discord dynamics in polarized environments.
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