activity
20162020
most citedPrivacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning

76 citations · 109 across the 5 of their papers we have counts for

collaborators

13 papers

cs.SI2020

A Feature-Driven Approach for Identifying Pathogenic Social Media Accounts

Hamidreza Alvari, Ghazaleh Beigi, Soumajyoti Sarkar +4

Over the past few years, we have observed different media outlets' attempts to shift public opinion by framing information to support a narrative that facilitate their goals. Malic…

cs.SI202014 cited

Social Science Guided Feature Engineering: A Novel Approach to Signed Link Analysis

Ghazaleh Beigi, Jiliang Tang, Huan Liu

Many real-world relations can be represented by signed networks with positive links (e.g., friendships and trust) and negative links (e.g., foes and distrust). Link prediction help…

cs.SI201976 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.CR201918 cited

I Am Not What I Write: Privacy Preserving Text Representation Learning

Ghazaleh Beigi, Kai Shu, Ruocheng Guo +2

Online users generate tremendous amounts of textual information by participating in different activities, such as writing reviews and sharing tweets. This textual data provides opp…

cs.SI20191 cited

Signed Link Prediction with Sparse Data: The Role of Personality Information

Ghazaleh Beigi, Suhas Ranganath, Huan Liu

Predicting signed links in social networks often faces the problem of signed link data sparsity, i.e., only a small percentage of signed links are given. The problem is exacerbated…

cs.SI2019

Less is More: Semi-Supervised Causal Inference for Detecting Pathogenic Users in Social Media

Hamidreza Alvari, Elham Shaabani, Soumajyoti Sarkar +2

Recent years have witnessed a surge of manipulation of public opinion and political events by malicious social media actors. These users are referred to as "Pathogenic Social Media…