The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications
Open accessAbstract
There is a large, popular, and growing literature on "scale-free" networks with the Internet along with metabolic networks representing perhaps the canonical examples. While this has in many ways reinvigorated graph theory, there is unfortunately no consistent, precise definition of scale-free graphs and few rigorous proofs of many of their claimed properties. In fact, it is easily shown that the existing theory has many inherent contradictions and that the most celebrated claims regarding the Internet and biology are verifiably false. In this paper, we introduce a structural metric that allows us to differentiate between all simple, connected graphs having an identical degree sequence, which is of particular interest when that sequence satisfies a power law relationship. We demonstrate that the proposed structural metric yields considerable insight into the claimed properties of SF graphs and provides one possible measure of _the extent to which a graph is scale-free_. This structural view can be related to previously studied graph properties such as the various notions of self-similarity, likelihood, betweenness and assortativity. Our approach clarifies much of the confusion surrounding the sensational qualitative claims in the current literature, and offers a rigorous and quantitative alternative, while suggesting the potential for a rich and interesting theory. This paper is aimed at readers familiar with the basics of Internet technology and comfortable with a theorem-proof style of exposition, but who may be unfamiliar with the existing literature on scale-free networks.
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Cites
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Measurement and analysis of online social networks
Mislove, A., Marcon, M., Gummadi, K. P., Druschel, P., & Bhattacharjee, B. (2007) · Proceedings of the 7th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1298306.1298311 · Cited by 3,057
Whole-brain anatomical networks: does the choice of nodes matter?
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Broido, A. D., & Clauset, A. (2019) · Nature Communications · doi:10.1038/s41467-019-08746-5 · Cited by 875
Disentangling Interactions in the Microbiome: A Network Perspective
Layeghifard, M., Hwang, D. M., & Guttman, D. S. (2017) · Trends in Microbiology · doi:10.1016/j.tim.2016.11.008 · Cited by 851
Biological network comparison using graphlet degree distribution
Pržulj, N. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btl301 · Cited by 837
Metadata
- Authors
- Li, L., Alderson, D., Doyle, J. C., & Willinger, W.
- Venue
- Internet Mathematics
- Publisher
- Internet Mathematics
- Published
- 2005-01
- Volume
- 2
- Issue
- 4
- Pages
- 431-523
- ISSN
- 1542-7951 (ISSN-L)
- 1944-9488
- OpenAlex
- W1987236914
- Cited by
- 519
- References
- 9
- FWCI
- 20.73
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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