Dynamic scaling, data-collapse and self-similarity in Barab\'asi-Albert networks

Abstract

In this article, we show that if each node of the Barab\'asi-Albert (BA) network is characterized by the generalized degree q, i.e. the product of their degree k and the square root of their respective birth time, then the distribution function F(q,t) exhibits dynamic scaling F(q,t→ ∞) t-1/2φ(q/t1/2) where φ(x) is the scaling function. We verified it by showing that a series of distinct F(q,t) vs q curves for different network sizes N collapse onto a single universal curve if we plot t1/2F(q,t) vs q/t1/2 instead. Finally, we show that the BA network falls into two universality classes depending on whether new nodes arrive with single edge (m=1) or with multiple edges (m>1).

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