Kleinberg's algorithm

Kleinberg's algorithm models how ideas, behaviors, or information spread through social networks. It captures the reality that most connections are local, but some links reach distant parts of the network, enabling rapid dissemination. The algorithm assigns probabilities to connections, favoring many short-range links and fewer long-range ones, following a specific pattern based on distance. This structure helps explain how influential 'super-spreaders' or 'hubs' facilitate quick and widespread diffusion, balancing local clustering with the occasional long-distance connection. It’s often used to understand phenomena like viral content spread or innovation adoption in social systems.