SmallWorldNetzwerke
SmallWorldNetzwerke are a class of networks characterized by high clustering among neighboring nodes and short average path lengths between any two nodes. They capture features observed in many real-world systems, such as social networks, biological networks, and technological infrastructures, where local groups are tightly interconnected yet distant nodes are still reachable quickly.
Origin and model: The concept was popularized by Watts and Strogatz in 1998, who proposed a simple
Key properties are the clustering coefficient C, which measures the tendency of neighbors to be connected,
Construction and variants: The Watts–Strogatz model is the canonical example, but many real systems show small-world
Applications and implications: Small-world networks are used to study information diffusion, epidemic spread, robustness, and synchronization.