most citedFake News Detection on Social Media: A Data Mining Perspective

601 citations · 658 across the 6 of their papers we have counts for

collaborators

6 papers

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.LG20199 cited

Graph Convolutional Networks with EigenPooling

Yao Ma, Suhang Wang, Charu C. Aggarwal +1

Graph neural networks, which generalize deep neural network models to graph structured data, have attracted increasing attention in recent years. They usually learn node representa…

cs.SI201917 cited

The Role of User Profile for Fake News Detection

Kai Shu, Xinyi Zhou, Suhang Wang +2

Consuming news from social media is becoming increasingly popular. Social media appeals to users due to its fast dissemination of information, low cost, and easy access. However, s…

cs.SI20171 cited

Signed Node Relevance Measurements

Tyler Derr, Chenxing Wang, Suhang Wang +1

In this paper, we perform the initial and comprehensive study on the problem of measuring node relevance on signed social networks. We design numerous relevance measurements for si…

cs.CL201712 cited

Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications

Fred Morstatter, Kai Shu, Suhang Wang +1

Most social media platforms are largely based on text, and users often write posts to describe where they are, what they are seeing, and how they are feeling. Because written text…

cs.SI2017601 cited

Fake News Detection on Social Media: A Data Mining Perspective

Kai Shu, Amy Sliva, Suhang Wang +2

Social media for news consumption is a double-edged sword. On the one hand, its low cost, easy access, and rapid dissemination of information lead people to seek out and consume ne…