1.6k citations · 2.4k across the 37 of their papers we have counts for
40 papers
Message passing for epidemiological interventions on networks with loops
Erik Weis, Laurent Hébert-Dufresne, Jean-Gabriel Young
Spreading models capture key dynamics on networks, such as cascading failures in economic systems, (mis)information diffusion, and pathogen transmission. Here, we focus on design i…
Sensitivity analysis of epidemic forecasting and spreading on networks with probability generating functions
Mariah C. Boudreau, William H. W. Thompson, Christopher M. Danforth +2
Epidemic forecasting tools embrace the stochasticity and heterogeneity of disease spread to predict the growth and size of outbreaks. Conceptually, stochasticity and heterogeneity…
One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories
Laurent Hébert-Dufresne, Yong-Yeol Ahn, Antoine Allard +15
From pathogens and computer viruses to genes and memes, contagion models have found widespread utility across the natural and social sciences. Despite their success and breadth of…
Governance as a complex, networked, democratic, satisfiability problem
Laurent Hébert-Dufresne, Nicholas W. Landry, Juniper Lovato +6
Democratic governments comprise a subset of a population whose goal is to produce coherent decisions, solving societal challenges while respecting the will of the people. New gover…
Symmetry-driven embedding of networks in hyperbolic space
Ariane Lizotte, Jean-Gabriel Young, Antoine Allard
Hyperbolic models are known to produce networks with properties observed empirically in most network datasets, including heavy-tailed degree distribution, high clustering, and hier…
Reconstructing networks from simple and complex contagions
Nicholas W. Landry, William Thompson, Laurent Hébert-Dufresne +1
Network scientists often use complex dynamic processes to describe network contagions, but tools for fitting contagion models typically assume simple dynamics. Here, we address thi…
Accurately summarizing an outbreak using epidemiological models takes time
B. K. M. Case, Jean-Gabriel Young, Laurent Hébert-Dufresne
Recent outbreaks of monkeypox and Ebola, and worrying waves of COVID-19, influenza and respiratory syncytial virus, have all led to a sharp increase in the use of epidemiological m…
Exact and rapid linear clustering of networks with dynamic programming
Alice Patania, Antoine Allard, Jean-Gabriel Young
We study the problem of clustering networks whose nodes have imputed or physical positions in a single dimension, for example prestige hierarchies or the similarity dimension of hy…
Compressing network populations with modal networks reveals structural diversity
Alec Kirkley, Alexis Rojas, Martin Rosvall +1
Analyzing relational data consisting of multiple samples or layers involves critical challenges: How many networks are required to capture the variety of structures in the data? An…
Hypergraph reconstruction from noisy pairwise observations
Ariane Lizotte, Jean-Gabriel Young, Antoine Allard
The network reconstruction task aims to estimate a complex system's structure from various data sources such as time series, snapshots, or interaction counts. Recent work has exami…
Network compression with configuration models and the minimum description length
Laurent Hébert-Dufresne, Jean-Gabriel Young, Alexander Daniels +2
Random network models, constrained to reproduce specific statistical features, are often used to represent and analyze network data and their mathematical descriptions. Chief among…
The OCEAN mailing list data set: Network analysis spanning mailing lists and code repositories
Melanie Warrick, Samuel F. Rosenblatt, Jean-Gabriel Young +3
Communication surrounding the development of an open source project largely occurs outside the software repository itself. Historically, large communities often used a collection o…
Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data
Caterina De Bacco, Martina Contisciani, Jonathan Cardoso-Silva +10
Social network data are often constructed by incorporating reports from multiple individuals. However, it is not obvious how to reconcile discordant responses from individuals. The…
The network epidemiology of an Ebola epidemic
Laurent Hébert-Dufresne, Jean-Gabriel Young, Jamie Bedson +8
Connecting the different scales of epidemic dynamics, from individuals to communities to nations, remains one of the main challenges of disease modeling. Here, we revisit one of th…
Clustering of heterogeneous populations of networks
Jean-Gabriel Young, Alec Kirkley, M. E. J. Newman
Statistical methods for reconstructing networks from repeated measurements typically assume that all measurements are generated from the same underlying network structure. This nee…
Which contributions count? Analysis of attribution in open source
Jean-Gabriel Young, Amanda Casari, Katie McLaughlin +3
Open source software projects usually acknowledge contributions with text files, websites, and other idiosyncratic methods. These data sources are hard to mine, which is why contri…
Impact and dynamics of hate and counter speech online
Joshua Garland, Keyan Ghazi-Zahedi, Jean-Gabriel Young +2
Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse. However, there is a lack of large-scale longitudinal studies…
Hypergraph reconstruction from network data
Jean-Gabriel Young, Giovanni Petri, Tiago P. Peixoto
Networks can describe the structure of a wide variety of complex systems by specifying which pairs of entities in the system are connected. While such pairwise representations are…
Bayesian inference of network structure from unreliable data
Jean-Gabriel Young, George T. Cantwell, M. E. J. Newman
Most empirical studies of complex networks do not return direct, error-free measurements of network structure. Instead, they typically rely on indirect measurements that are often…
Countering hate on social media: Large scale classification of hate and counter speech
Joshua Garland, Keyan Ghazi-Zahedi, Jean-Gabriel Young +2
Hateful rhetoric is plaguing online discourse, fostering extreme societal movements and possibly giving rise to real-world violence. A potential solution to this growing global pro…
Networks beyond pairwise interactions: structure and dynamics
Federico Battiston, Giulia Cencetti, Iacopo Iacopini +5
The complexity of many biological, social and technological systems stems from the richness of the interactions among their units. Over the past decades, a great variety of complex…
A Clarified Typology of Core-Periphery Structure in Networks
Ryan J. Gallagher, Jean-Gabriel Young, Brooke Foucault Welles
Core-periphery structure, the arrangement of a network into a dense core and sparse periphery, is a versatile descriptor of various social, biological, and technological networks.…
Inference for growing trees
George T. Cantwell, Guillaume St-Onge, Jean-Gabriel Young
One can often make inferences about a growing network from its current state alone. For example, it is generally possible to determine how a network changed over time or pick among…
Interacting contagions are indistinguishable from social reinforcement
Laurent Hébert-Dufresne, Samuel V. Scarpino, Jean-Gabriel Young
From fake news to innovative technologies, many contagions spread via a process of social reinforcement, where multiple exposures are distinct from prolonged exposure to a single s…