Netzarten

Netzarten is a term used in network science to describe categories or typologies of networks. It serves as a framework for organizing networks by structure, function, and dynamics, allowing analysts to compare systems across domains such as technology, biology, and society.

Topology-oriented Netzarten classify networks by how nodes are connected. Common classes include random networks (Erdős–Rényi), small-world networks (high clustering, short path lengths, Watts–Strogatz), and scale-free networks (power-law degree distributions, Barabási–Albert). Other topologies include lattice, modular, and hierarchical networks.

Function-oriented Netzarten group networks by purpose: social networks, communication networks, transportation networks, and biological networks such as metabolic, gene regulatory, or neural networks.

Dynamics-oriented Netzarten address temporal evolution and layering. Some networks are static, others evolve through growth or rewiring. Multiplex or multilayer networks model entities connected in several layers (for example social and transportation links), while temporal networks emphasize time-stamped interactions.

Analytical methods and metrics associated with Netzarten include degree distribution, clustering coefficient, average path length, centrality measures, and robustness. Researchers apply graph theory, statistics, and simulation to study diffusion, contagion, and resilience within a given network type.

Understanding a network’s Netzart informs modeling choices and intervention strategies in fields such as infrastructure planning, epidemiology, information diffusion, marketing, and neuroscience.