Search Results for author:
Found 24 papers, 14 papers with code
Distinguishing In-Groups and Onlookers by Language Use
Inferring group membership of social media users is of high interest in many domains.
Temporal and probabilistic comparisons of epidemic interventions
Forecasting disease spread is a critical tool to help public health officials design and plan public health interventions. However, the expected future state of an epidemic is not necessarily well defined as disease spread is inherently stochastic, contact patterns within a population are heterogeneous, and behaviors change.
Accurately summarizing an outbreak using epidemiological models takes time
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 models to estimate key epidemiological parameters.
The network epidemiology of an Ebola epidemic
We leverage the data collected by the surveillance and contact tracing protocols of the Sierra Leone Ministry of Health and Sanitation, the US Centers for Disease Control and Prevention, and other responding partners to validate a network epidemiology framework connecting the population (incidence), community (local forecasts), and individual (secondary infections) scales of disease transmission.
Immunity-induced criticality of the genotype network of influenza A (H3N2) hemagglutinin
We argue that: (i) genotype networks are driven by mutation and host immunity to explore a subspace of networks predictable in structure, and (ii) genotype networks provide an underlying structure necessary to capture the rich dynamics of multistrain epidemic models.
Predicting the diversity of early epidemic spread on networks
We show how the challenge of inferring the early course of an epidemic falls on the randomness of disease spread more so than on the heterogeneity of contact patterns.
Universal nonlinear infection kernel from heterogeneous exposure on higher-order networks
The colocation of individuals in different environments is an important prerequisite for exposure to infectious diseases on a social network.
Physics and Society Adaptation and Self-Organizing Systems
Containing Future Epidemics with Trustworthy Federated Systems for Ubiquitous Warning and Response
In this sense, we expect active participation of empowered citizens to supplement the more usual top-down management of epidemics.
Distributed, Parallel, and Cluster Computing
Impact and dynamics of hate and counter speech online
Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse.
Network comparison and the within-ensemble graph distance
Quantifying the differences between networks is a challenging and ever-present problem in network science.
Physics and Society Social and Information Networks
Localization, epidemic transitions, and unpredictability of multistrain epidemics with an underlying genotype network
Mathematical disease modelling has long operated under the assumption that any one infectious disease is caused by one transmissible pathogen spreading among a population.
Countering hate on social media: Large scale classification of hate and counter speech
Hateful rhetoric is plaguing online discourse, fostering extreme societal movements and possibly giving rise to real-world violence.
Stochasticity and heterogeneity in the transmission dynamics of SARS-CoV-2
SARS-CoV-2 causing COVID-19 disease has moved rapidly around the globe, infecting millions and killing hundreds of thousands.
Social confinement and mesoscopic localization of epidemics on networks
Recommendations around epidemics tend to focus on individual behaviors, with much less efforts attempting to guide event cancellations and other collective behaviors since most models lack the higher-order structure necessary to describe large gatherings.
Physics and Society Adaptation and Self-Organizing Systems
Beyond $R_0$: Heterogeneity in secondary infections and probabilistic epidemic forecasting
Lastly, we demonstrate that without data on the heterogeneity in secondary infections for emerging infectious diseases like COVID-19, the uncertainty in outbreak size ranges dramatically.
Populations and Evolution Applied Physics Physics and Society
On the accuracy of message-passing approaches to percolation in complex networks
In fact we find that the closer a non-tree network is to a tree, the worse the MPA accuracy becomes.
Physics and Society Statistical Mechanics
Interacting contagions are indistinguishable from social reinforcement
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 source.
Physics and Society Dynamical Systems Populations and Evolution
Smeared phase transitions in percolation on real complex networks
Our results shed light not only on the nature of the percolation transition in complex systems, but also provide two important insights on the numerical and analytical tools we use to study them.
Physics and Society Disordered Systems and Neural Networks
Efficient sampling of spreading processes on complex networks using a composition and rejection algorithm
Efficient stochastic simulation algorithms are of paramount importance to the study of spreading phenomena on complex networks.
Physics and Society Social and Information Networks
Percolation and the effective structure of complex networks
Analytical approaches to model the structure of complex networks can be distinguished into two groups according to whether they consider an intensive (e. g., fixed degree sequence and random otherwise) or an extensive (e. g., adjacency matrix) description of the network structure.
Physics and Society Statistical Mechanics
Phase transition in the recoverability of network history
Network growth processes can be understood as generative models of the structure and history of complex networks.
Finite size analysis of the detectability limit of the stochastic block model
We then distinguish the concept of average detectability from the concept of instance-by-instance detectability and give explicit formulas for both definitions.
Physics and Society Information Theory Information Theory
Dynamics of beneficial epidemics
Third, in the context of dynamic social networks, we find that preferences for increased global infection accelerate spread and produce superexponential fixation, but preferences for local assortativity halt epidemics by disconnecting the infected from the susceptible.
Physics and Society Multiagent Systems Social and Information Networks Adaptation and Self-Organizing Systems Populations and Evolution
Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition
The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores.
Physics and Society Disordered Systems and Neural Networks Discrete Mathematics Social and Information Networks Combinatorics
