activity
20162023
most citedLearning Fair Node Representations with Graph Counterfactual Fairness

77 citations · 429 across the 30 of their papers we have counts for

collaborators
Showing cs.SIShow all

10 papers · 1 filter

cs.SI2022★ 1 cited

Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks

Ujun Jeong, Kaize Ding, Lu Cheng +3

Nowadays, fake news easily propagates through online social networks and becomes a grand threat to individuals and society. Assessing the authenticity of news is challenging due to…

cs.SI2019★ 76 cited

Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning

Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo +3

Recommendation is one of the critical applications that helps users find information relevant to their interests. However, a malicious attacker can infer users' private information…

cs.SI2019

Learning Individual Causal Effects from Networked Observational Data

Ruocheng Guo, Jundong Li, Huan Liu

Convenient access to observational data enables us to learn causal effects without randomized experiments. This research direction draws increasing attention in research areas such…

cs.SI2019

Detecting Pathogenic Social Media Accounts without Content or Network Structure

Elham Shaabani, Ruocheng Guo, Paulo Shakarian

The spread of harmful mis-information in social media is a pressing problem. We refer accounts that have the capability of spreading such information to viral proportions as "Patho…

cs.SI2019★ 1 cited

Using network motifs to characterize temporal network evolution leading to diffusion inhibition

Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian

Network motifs are patterns of over-represented node interactions in a network which have been previously used as building blocks to understand various aspects of the social networ…

cs.SI2018

Understanding and forecasting lifecycle events in information cascades

Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian

Most social network sites allow users to reshare a piece of information posted by a user. As time progresses, the cascade of reshares grows, eventually saturating after a certain t…