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20112023
most citedInvestigating and Mitigating Degree-Related Biases in Graph Convolutional Networks

96 citations · 415 across the 46 of their papers we have counts for

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7 papers · 1 filter

cs.SI2023★ 9 cited

Heterogeneous Social Event Detection via Hyperbolic Graph Representations

Zitai Qiu, Jia Wu, Jian Yang +2

Social events reflect the dynamics of society and, here, natural disasters and emergencies receive significant attention. The timely detection of these events can provide organisat…

cs.SI2019★ 12 cited

Meta Diagram based Active Social Networks Alignment

Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang

Network alignment aims at inferring a set of anchor links matching the shared entities between different information networks, which has become a prerequisite step for effective fu…

cs.SI2018★ 12 cited

Multi-dimensional Graph Convolutional Networks

Yao Ma, Suhang Wang, Charu C. Aggarwal +2

Convolutional neural networks (CNNs) leverage the great power in representation learning on regular grid data such as image and video. Recently, increasing attention has been paid…

cs.SI2017★ 3 cited

Signed Network Modeling Based on Structural Balance Theory

Tyler Derr, Charu Aggarwal, Jiliang Tang

The modeling of networks, specifically generative models, have been shown to provide a plethora of information about the underlying network structures, as well as many other benefi…

cs.SI2015★ 13 cited

A Survey of Signed Network Mining in Social Media

Jiliang Tang, Yi Chang, Charu Aggarwal +1

Many real-world relations can be represented by signed networks with positive and negative links, as a result of which signed network analysis has attracted increasing attention fr…

cs.SI2014★ 1 cited

Negative Link Prediction in Social Media

Jiliang Tang, Shiyu Chang, Charu Aggarwal +1

Signed network analysis has attracted increasing attention in recent years. This is in part because research on signed network analysis suggests that negative links have added valu…

cs.SI2012★ 1 cited

Learning from Collective Intelligence in Groups

Guo-Jun Qi, Charu Aggarwal, Pierre Moulin +1

Collective intelligence, which aggregates the shared information from large crowds, is often negatively impacted by unreliable information sources with the low quality data. This b…