The structure of networks that evolve under a combination of growth, via node addition and random attachment, and contraction, via random node deletion
This paper presents analytical results for the time-dependent and asymptotic degree distributions of networks evolving under a balance of random node addition and deletion, revealing that while growing networks converge to a steady-state distribution with a Poisson-like tail, contracting networks exhibit distinct convergence behaviors depending on the specific rate of contraction relative to the network's eventual disappearance.