Modeling multi-opinion propagation in complex systems with heterogeneous relationships via Potts model on signed...

Area of Science:

• Complex Systems
• Network Science
• Sociophysics

Background:

• Understanding opinion dynamics in populations with diverse relationships is crucial.
• Signed networks capture both positive and negative interactions, offering a richer model than traditional networks.
• The Potts model, adapted from physics, can simulate multi-state interactions and coevolution.

Purpose of the Study:

• To investigate how heterogeneous relationships influence the spread of diverse opinions.
• To analyze the role of negative edges in complex systems with contradictory interactions.
• To explore the impact of network topology on opinion consensus and system balance.

Main Methods:

• Application of the Potts model on signed networks to simulate multi-opinion propagation.
• Analysis and experimentation on both synthetic and real-world signed networks.
• Examination of network topology, community structure, and edge properties.

Main Results:

• The proportion and location of negative edges, not initial opinions, determine consensus formation.
• Network topology influences the critical ratio of negative edges, leading to consensus or multiparty situations.
• A small number of negative edges can unexpectedly disrupt consensus; community structures shape inter-group dynamics.

Conclusions:

• Logically contradictory interactions profoundly affect collective behaviors and opinion propagation.
• Findings offer insights into controlling multi-opinion spread and enhancing system balance in social networks.
• Network structural balance increases dynamically, leading to dominant high-order structures.