Scale-free networks arise from power-law degree distributions. Due to the finite size of real-world networks, the power law inevitably has a cutoff at some maximum degree Δ. We investigate the relative size of the giant component S in the large-network limit. We show that S as a function of Δ increases fast when Δ is just large enough for the giant component to exist, but increases ever more slowly when Δ increases further. This gives that while the degree distribution converges to a pure power law when Δ → ∞, S approaches its limiting value at a slow pace. The convergence rate also depends on the power-law exponent τ of the degree distribution. The worst rate of convergence is found to be for the case , which concerns many of the real-world networks reported in the literature.
|Publication status||Published - 2015|