The nature and nurture of network evolution

Area of Science:

• Network Science
• Statistical Physics
• Sociology

Background:

• The fat-tail characteristic in complex network degree distributions is well-studied.
• However, the drivers of degree distribution across all degrees remain unclear.

Purpose of the Study:

• To propose a novel evolution model for complex networks.
• To explain the complete degree distribution using node-specific factors.

Main Methods:

• Developed an evolution model incorporating node weight (nature) and node degree (nurture).
• Validated the model against degree and degree ratio distributions of real-world networks.
• Analyzed network evolution processes.

Main Results:

• The proposed model accurately fits numerous real-world network degree distributions.
• The model successfully reproduces observed network evolution processes.
• Identified distinct dominant factors for social versus non-social networks.

Conclusions:

• Node weight (nature) and degree (nurture) are key to understanding network evolution.
• Nurture is dominant in social networks (e.g., human interactions).
• Nature is dominant in non-social networks (e.g., technological systems).