Open Access
February 2021 A Statistical Framework for Modern Network Science
Harry Crane, Walter Dempsey
Statist. Sci. 36(1): 51-67 (February 2021). DOI: 10.1214/19-STS759


We discuss how sampling design, units, the observation mechanism and other basic statistical notions figure into modern network data analysis. These considerations pose several new challenges that cannot be adequately addressed by merely extending or generalizing classical methods. Such challenges stem from fundamental differences between the domains in which network data emerge and those for which classical tools were developed. By revisiting these basic statistical considerations, we suggest a framework in which to develop theory and methods for network analysis in a way that accounts for both conceptual and practical challenges of network science. We then discuss how some well-known model classes fit within this framework.


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Harry Crane. Walter Dempsey. "A Statistical Framework for Modern Network Science." Statist. Sci. 36 (1) 51 - 67, February 2021.


Published: February 2021
First available in Project Euclid: 21 December 2020

MathSciNet: MR4194203
Digital Object Identifier: 10.1214/19-STS759

Keywords: data generating process , edge exchangeable network , network data , network sampling , relational exchangeability , relative exchangeability , Scale-free network , sparse network

Rights: Copyright © 2021 Institute of Mathematical Statistics

Vol.36 • No. 1 • February 2021
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