Paper Info
Title
Scale-free networks are rare.
Abstract
Real-world networks are often claimed to be scale free, meaning that the fraction of nodes with degree k follows a power law k(-alpha), a pattern with broad implications for the structure and dynamics of complex systems. However, the universality of scale-free networks remains controversial. Here, we organize different definitions of scale-free networks and construct a severe test of their empirical prevalence using state-of-the-art statistical tools applied to nearly 1000 social, biological, technological, transportation, and information networks. Across these networks, we find robust evidence that strongly scale-free structure is empirically rare, while for most networks, log-normal distributions fit the data as well or better than power laws. Furthermore, social networks are at best weakly scale free, while a handful of technological and biological networks appear strongly scale free. These findings highlight the structural diversity of real-world networks and the need for new theoretical explanations of these non-scale-free patterns.
Year
DOI
Venue
2018
10.1038/s41467-019-08746-5
NATURE COMMUNICATIONS
Field
DocType
Volume
Information system,Data science,Complex system,Information networks,Social network,Biology,Biological network,Scale-free network,Genetics,Universality (philosophy),Power law
Journal
10
ISSN
Citations 
PageRank 
2041-1723
21
0.81
References 
Authors
22
2
Name
Order
Citations
PageRank
Anna D. Broido1210.81
Aaron Clauset22033146.18