Austin R Benson
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Explore the profile of Austin R Benson including associated specialties, affiliations and a list of published articles.
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7
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207
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Recent Articles
1.
Veldt N, Benson A, Kleinberg J
Sci Adv
. 2023 Jan;
9(1):eabq3200.
PMID: 36608141
Homophily is the seemingly ubiquitous tendency for people to connect and interact with other individuals who are similar to them. This is a well-documented principle and is fundamental for how...
2.
Chodrow P, Veldt N, Benson A
Sci Adv
. 2021 Jul;
7(28).
PMID: 34233880
Hypergraphs are a natural modeling paradigm for networked systems with multiway interactions. A standard task in network analysis is the identification of closely related or densely interconnected nodes. We propose...
3.
Benson A, Abebe R, Schaub M, Jadbabaie A, Kleinberg J
Proc Natl Acad Sci U S A
. 2018 Nov;
115(48):E11221-E11230.
PMID: 30413619
Networks provide a powerful formalism for modeling complex systems by using a model of pairwise interactions. But much of the structure within these systems involves interactions that take place among...
4.
Yin H, Benson A, Leskovec J
Phys Rev E
. 2018 Jun;
97(5-1):052306.
PMID: 29906904
A fundamental property of complex networks is the tendency for edges to cluster. The extent of the clustering is typically quantified by the clustering coefficient, which is the probability that...
5.
Yin H, Benson A, Leskovec J, Gleich D
KDD
. 2018 May;
2017:555-564.
PMID: 29770258
Local graph clustering methods aim to find a cluster of nodes by exploring a small region of the graph. These methods are attractive because they enable targeted clustering around a...
6.
Benson A, Gleich D, Leskovec J
Science
. 2016 Jul;
353(6295):163-6.
PMID: 27387949
Networks are a fundamental tool for understanding and modeling complex systems in physics, biology, neuroscience, engineering, and social science. Many networks are known to exhibit rich, lower-order connectivity patterns that...
7.
Benson A, Gleich D, Leskovec J
Proc SIAM Int Conf Data Min
. 2015 Jan;
2015:118-126.
PMID: 27812399
Spectral graph theory-based methods represent an important class of tools for studying the structure of networks. Spectral methods are based on a first-order Markov chain derived from a random walk...