40 citations · 54 across the 14 of their papers we have counts for
20 papers
Learning Social Influence with Unobserved Attention
William Thompson, Moyi Tian, Linh Huynh +4
Social influence, the tendency of our social environment to sway our beliefs and behaviors, is often cited as a driver of population-level trends in opinions or beliefs. Many quant…
Measuring Diversity and Segregation with Convex Functions
Philip S. Chodrow
The problem of segregation measurement is to quantitatively describe the interaction of a population's attributes (such as race, ethnicity, education level, or income) with a separ…
Growing Hypergraphs with Homophily
Violet Ross, Francis Cataldo, Philip S. Chodrow
There are many extant models of hypergraphs with interactions governed by attribute-based homophily between nodes, but most assume independence between edges conditional on node pa…
Modeling Social Systems: Transparency, Reproducibility, and Responsibility
Maximino Aldana, Roni Barak Ventura, Heather Z. Brooks +13
Mathematical models of complex social systems can enrich social scientific theory, inform interventions, and shape policy. From voting behavior to economic inequality and urban dev…
The illusion of households as entities in social networks
Izabel Aguiar, Philip S. Chodrow, Johan Ugander
Data recording connections between people in communities and villages are collected and analyzed in various ways, most often as either networks of individuals or as networks of hou…
Edge Correlations and Link Prediction in Growing Hypergraphs
Xie He, Philip S. Chodrow, Peter J. Mucha
We propose a generative model of temporally-evolving hypergraphs in which hyperedges form via noisy copying of previous hyperedges. Our proposed model reproduces several stylized f…
Equivalence of Informations Characterizes Bregman Divergences
Philip S. Chodrow
Bregman divergences are a class of distance-like comparison functions which play fundamental roles in optimization, statistics, and information theory. One important property of Br…
Community Detection in Hypergraphs via Mutual Information Maximization
Jurgen Kritschgau, Daniel Kaiser, Oliver Alvarado Rodriguez +7
The hypergraph community detection problem seeks to identify groups of related nodes in hypergraph data. We propose an information-theoretic hypergraph community detection algorith…
Data science and social justice in the mathematics community
Quindel Jones, Andrés R. Vindas Meléndez, Ariana Mendible +5
Data science for social justice (DS4SJ) is data-scientific work that supports the liberation of oppressed and marginalized people. By nature, this work lies at the intersection of…
Emergence of polarization in a sigmoidal bounded-confidence model of opinion dynamics
Heather Z. Brooks, Philip S. Chodrow, Mason A. Porter
We study a nonlinear bounded-confidence model (BCM) of continuous-time opinion dynamics on networks with both persuadable individuals and zealots. The model is parameterized by a s…
Nonbacktracking spectral clustering of nonuniform hypergraphs
Philip Chodrow, Nicole Eikmeier, Jamie Haddock
Spectral methods offer a tractable, global framework for clustering in graphs via eigenvector computations on graph matrices. Hypergraph data, in which entities interact on edges o…
Generative hypergraph clustering: from blockmodels to modularity
Philip S. Chodrow, Nate Veldt, Austin R. Benson
Hypergraphs are a natural modeling paradigm for a wide range of complex relational systems. A standard analysis task is to identify clusters of closely related or densely interconn…
Emergence of Hierarchy in Networked Endorsement Dynamics
Mari Kawakatsu, Philip S. Chodrow, Nicole Eikmeier +1
Many social and biological systems are characterized by enduring hierarchies, including those organized around prestige in academia, dominance in animal groups, and desirability in…
Annotated Hypergraphs: Models and Applications
Philip Chodrow, Andrew Mellor
Hypergraphs offer a natural modeling language for studying polyadic interactions between sets of entities. Many polyadic interactions are asymmetric, with nodes playing distinctive…
Moments of Uniform Random Multigraphs with Fixed Degree Sequences
Philip S. Chodrow
We study the expected adjacency matrix of a uniformly random multigraph with fixed degree sequence . This matrix arises in a variety of analyses of n…
Configuration Models of Random Hypergraphs
Philip S. Chodrow
Many empirical networks are intrinsically polyadic, with interactions occurring within groups of agents of arbitrary size. There are, however, few flexible null models that can sup…
Log-minor distributions and an application to estimating mean subsystem entropy
Alice C. Schwarze, Philip S. Chodrow, Mason A. Porter
A common task in physics, information theory, and other fields is the analysis of properties of subsystems of a given system. Given the covariance matrix of a system of cou…
Local Symmetry and Global Structure in Adaptive Voter Models
Philip S. Chodrow, Peter J. Mucha
Adaptive voter models (AVMs) are simple mechanistic systems that model the emergence of mesoscopic structure from local networked processes driven by conflict and homophily. AVMs d…
Divergence, Entropy, Information: An Opinionated Introduction to Information Theory
Philip Chodrow
Information theory is a mathematical theory of learning with deep connections with topics as diverse as artificial intelligence, statistical physics, and biological evolution. Many…
Upper and lower bounds for the iterates of order-preserving homogeneous maps on cones
Philip Chodrow, Cole Franks, Brian Lins
We define upper bound and lower bounds for order-preserving homogeneous of degree one maps on a proper closed cone in in terms of the cone spectral radius. We also define we…