WattsStrogatzin

WattsStrogatzin is a term that appears in some discussions as a variant spelling or informal reference to the Watts–Strogatz small-world network model developed by Duncan Watts and Steven Strogatz in 1998. It is not a distinct, widely recognized model in its own right, and most scholarly attention treats the Watts–Strogatz framework under a single conventional name. When encountered, the term often points to the same core ideas or to a minor alteration described by authors using an informal label.

The Watts–Strogatz model describes a method for generating graphs that combine high clustering with short average path lengths. The construction begins with a regular ring lattice in which each node connects to k nearest neighbors. Then each undirected edge is rewired with probability p to a randomly chosen node, with constraints to avoid self-loops and duplicate edges. For p equal to 0, the network is a regular lattice; for p close to 1, it approaches a random graph. For intermediate values of p, the resulting networks exhibit small-world properties: clustering remains relatively high while the average shortest path length drops dramatically.

Variants associated with the term WattsStrogatzin may refer to extensions of the original idea, such as directed edges, weighted connections, or temporal dynamics, though these are typically described as modifications to the Watts–Strogatz framework rather than separate models. Researchers may also adapt parameters like the degree k and rewiring probability p to suit specific application domains.

Applications of Watts–Strogatz-type networks span social science, neuroscience, epidemiology, and information networks, where small-world connectivity influences diffusion, synchronization, and robustness. See also Watts–Strogatz model, small-world networks. The original foundational work is Watts and Strogatz (1998).