A model for analyzing competitive dynamics on triplex networks

Area of Science:

• Complex Systems Science
• Network Science
• Computational Social Science

Background:

• Competitive dynamics are crucial in multi-layer systems.
• Existing models often focus on single-layer networks.
• Understanding inter-layer competition is key for complex network evolution.

Purpose of the Study:

• To propose and analyze a novel triplex complex network model.
• To investigate the evolution of competitive dynamics across multiple network layers.
• To identify factors influencing network competitiveness and stability.

Main Methods:

• Development of a triplex network model integrating opinion diffusion, Ising, and signed network concepts.
• Derivation of the model's evolution process and dynamical equations.
• Extensive numerical simulations to explore parameter influences.

Main Results:

• Higher global transition thresholds and initial active nodes increase surviving layers and node activity.
• Correlations identified between initial active nodes, average degree, and network competitiveness.
• Network topology significantly impacts competitiveness, with specific conditions identified for optimal performance.

Conclusions:

• The proposed triplex network model provides insights into competitive dynamics in multi-layer systems.
• Strategies involving initial node activation and network structure can enhance platform competitiveness.
• Findings offer practical suggestions for improving real-world platform competitiveness.