Voter-like Dynamics with Conflicting Preferences on Modular Networks

Area of Science:

• Social dynamics
• Network science
• Opinion formation

Background:

• Individual opinions are shaped by social coordination and personal biases.
• Understanding the interplay between network topology and these factors is crucial for opinion dynamics.

Purpose of the Study:

• To investigate an extended voter model incorporating two populations with opposing preferences.
• To analyze the impact of modular network structures, modeling epistemic bubbles, on opinion consensus and polarization.

Main Methods:

• Utilized approximate analytical methods and computer simulations.
• Employed a modular graph structure with two communities reflecting bias assignments.
• Compared mean-field approximation with pair approximation and validated on a real network.

Main Results:

• The system can reach either a consensus or a polarized state, depending on network and bias strengths.
• Modular structures generally increase polarization and its parameter range.
• High bias strength differences lead to opinion imposition dependent on the segregated population's structure.

Conclusions:

• Network modularity significantly influences opinion polarization and consensus.
• Population segregation plays a key role in opinion dynamics when bias strengths differ significantly.
• The study provides insights into opinion formation within structured social networks.