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20 April 2024 |
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Article overview
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Challenging the assumption of simple scaling in the observables of network growth | | Max Falkenberg
; Jong-Hyeok Lee
; Shun-ichi Amano
; Ken-ichiro Ogawa
; Kazuo Yano
; Yoshihiro Miyake
; Tim S. Evans
; Kim Christensen
; | | Date: |
24 Jan 2020 | | Abstract: | Identifying power law scaling in real networks - indicative of preferential
attachment - has proved controversial. Critics argue that directly measuring
the temporal evolution of a network is better than measuring the degree
distribution when looking for preferential attachment. However, many of the
established methods do not account for any potential time-dependence in the
attachment kernels of growing networks, or assume that the node degree is the
key observable determining node evolution. In this paper, we argue that these
assumptions may lead to misleading conclusions about the future evolution, and
past origin, of these networks. We illustrate the risks of these assumptions by
introducing a simple adaptation of the Barabasi-Albert model, the ’’k2 model’’,
where new nodes attach to nodes in the existing network proportionally to the
number of nodes within distance two of the target node, the effect of which we
demonstrate both numerically and analytically. This k2 model results in time
dependent degree distributions and attachment kernels, despite initially
appearing to grow as linear preferential attachment. We support these results
by showing that similar effects are seen in real networks using the American
Physical Society citation network. Our results suggest that significantly more
care should go into the analysis of the evolution of growing networks, and that
existing results regarding the evolution of growing networks may be false. | | Source: | arXiv, 2001.9118 | | Services: | Forum | Review | PDF | Favorites | |
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