1.3k citations · 3.7k across the 55 of their papers we have counts for
10 papers · 1 filter
Link Prediction in Networks with Core-Fringe Data
Austin R. Benson, Jon Kleinberg
Data collection often involves the partial measurement of a larger system. A common example arises in collecting network data: we often obtain network datasets by recording all of…
Choosing to Grow a Graph: Modeling Network Formation as Discrete Choice
Jan Overgoor, Austin R. Benson, Johan Ugander
We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is…
A sampling framework for counting temporal motifs
Paul Liu, Austin Benson, Moses Charikar
Pattern counting in graphs is fundamental to network science tasks, and there are many scalable methods for approximating counts of small patterns, often called motifs, in large gr…
Random Spatial Network Models with Core-Periphery Structure
Junteng Jia, Austin R. Benson
Core-periphery structure is a common property of complex networks, which is a composition of tightly connected groups of core vertices and sparsely connected periphery vertices. Th…
Three hypergraph eigenvector centralities
Austin R. Benson
Eigenvector centrality is a standard network analysis tool for determining the importance of (or ranking of) entities in a connected system that is represented by a graph. However,…
Random Walks on Simplicial Complexes and the normalized Hodge 1-Laplacian
Michael T. Schaub, Austin R. Benson, Paul Horn +2
Focusing on coupling between edges, we generalize the relationship between the normalized graph Laplacian and random walks on graphs by devising an appropriate normalization for th…
Found Graph Data and Planted Vertex Covers
Austin R. Benson, Jon Kleinberg
A typical way in which network data is recorded is to measure all the interactions among a specified set of core nodes; this produces a graph containing this core together with a p…
Computing tensor Z-eigenvectors with dynamical systems
Austin R. Benson, David F. Gleich
We present a new framework for computing Z-eigenvectors of general tensors based on numerically integrating a dynamical system that can only converge to a Z-eigenvector. Our motiva…
Tools for higher-order network analysis
Austin R. Benson
Networks are a fundamental model of complex systems throughout the sciences, and network datasets are typically analyzed through lower-order connectivity patterns described at the…
Simplicial Closure and higher-order link prediction
Austin R. Benson, Rediet Abebe, Michael T. Schaub +2
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 t…