stanom

Stanom is a term used in theoretical discussions of information dynamics and online discourse. In that context, stanom refers to a unitless measure of topic stability: the degree to which a subject remains central in a network’s conversation after accounting for external shocks such as events, platform changes, or keyword trends.

Origin and usage of the term are not well documented. It has appeared in speculative writings and online discussions as a neologism formed to discuss stability in diffusion processes; some commentators describe it as a portmanteau of "stasis" and "nominal" or simply a variable name chosen for modeling.

Conceptually, stanom is imagined to be derived from time-series data on engagement, such as mentions, shares, or reactions, aggregated across nodes in a network. In simplified models, stanom can be viewed as the long-run equilibrium level of topic attention: high stanom indicates persistence, while low stanom indicates rapid decay or volatility.

Stanom serves as a theoretical tool for exploring how certain topics withstand perturbations. It is not a standard metric in empirical social science, and there is no universally accepted method to estimate it from real data. Its usefulness depends on assumptions about the network, user behavior, and platform algorithms, which can bias estimates.

Related concepts include stickiness, attention inertia, and diffusion stability in information propagation models.