• Publications
  • Influence
Information Contagion: An Empirical Study of the Spread of News on Digg and Twitter Social Networks
It is shown that social networks play a crucial role in the spread of information on these sites, and that network structure affects dynamics of information flow.
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
This work proposes a new model, MixHop, that can learn a general class of neighborhood mixing relationships by repeatedly mixing feature representations of neighbors at various distances, and proposes sparsity regularization that allows to visualize how the network prioritizes neighborhood information across different graph datasets.
A Survey on Bias and Fairness in Machine Learning
This survey investigated different real-world applications that have shown biases in various ways, and created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems.
Using a model of social dynamics to predict popularity of news
It is shown that stochastic models of user behavior on these sites allows predicting popularity based on early user reactions to new content, and that incorporating aspects of the web site design improves on predictions based on simply extrapolating from the early votes.
Mathematical Model of Foraging in a Group of Robots: Effect of Interference
A mathematical model of foraging in a homogeneous multi-robot system, with the goal of understanding quantitatively the effects of interference, is presented and an optimal group size is found that maximizes group performance.
Analysis of Dynamic Task Allocation in Multi-Robot Systems
A mathematical model of a general dynamic task allocation mechanism that allows robots to choose between two types of tasks and the effect that the number of observations and the choice of the decision function have on the performance of the system is presented.
Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set
Background At the time of this writing, the coronavirus disease (COVID-19) pandemic outbreak has already put tremendous strain on many countries' citizens, resources, and economies around the world.
Social Browsing on Flickr
Through an extensive analysis of Flickr data, it is shown that social browsing through the contacts' photo streams is one of the primary methods by which users find new images on Flickr.
The DARPA Twitter Bot Challenge
There is a need to identify and eliminate "influence bots" - realistic, automated identities that illicitly shape discussions on sites like Twitter and Facebook - before they get too influential.
The Simple Rules of Social Contagion
A framework is provided for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior and significantly simplifies the dynamics of social contagion.