Spreadnél

Spreadnél is a term used in discussions of diffusion processes to describe the rate at which a phenomenon spreads through a network under specified conditions. It is a neutral, conceptual metric rather than a fixed natural-law quantity, and its precise definition can vary by context. In this article, spreadnél is defined as the expected number of new adopters generated by a single adopter over a defined time window within a given population and network structure.

Conceptually, spreadnél is analogous to reproduction numbers used in epidemiology, but it is content- and platform-specific. Its value depends on factors such as network topology (for example, how densely nodes are connected), user behavior, content appeal, and the influence of algorithms or moderation policies. Because these factors change over time, spreadnél is often treated as time-varying and context-dependent rather than a single constant.

Measurement and calculation typically involve tracking adoption events within a cohort over successive time steps. The metric is estimated by counting the number of newly influenced individuals per existing adopter within the chosen window, and then averaging across adopters. Confidence intervals or Bayesian methods may be applied to reflect uncertainty due to incomplete observation or heterogeneity in the network.

Applications of spreadnél include evaluating marketing campaigns, public information initiatives, and studies of misinformation spread. Limitations include the need for clear definitions of “adoption,” the dependence on observed data quality, and the potential for differing results across networks and content types.

See also: diffusion of innovations, information diffusion, reproduction number, Rt.