240 citations · 449 across the 5 of their papers we have counts for
5 papers
Let Silence Speak: Enhancing Fake News Detection with Generated Comments from Large Language Models
Qiong Nan, Qiang Sheng, Juan Cao +3
Fake news detection plays a crucial role in protecting social media users and maintaining a healthy news ecosystem. Among existing works, comment-based fake news detection methods…
Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting
Qiong Nan, Qiang Sheng, Juan Cao +4
Both accuracy and timeliness are key factors in detecting fake news on social media. However, most existing methods encounter an accuracy-timeliness dilemma: Content-only methods g…
Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer
Qiong Nan, Danding Wang, Yongchun Zhu +4
Both real and fake news in various domains, such as politics, health, and entertainment are spread via online social media every day, necessitating fake news detection for multiple…
Memory-Guided Multi-View Multi-Domain Fake News Detection
Yongchun Zhu, Qiang Sheng, Juan Cao +5
The wide spread of fake news is increasingly threatening both individuals and society. Great efforts have been made for automatic fake news detection on a single domain (e.g., poli…
MDFEND: Multi-domain Fake News Detection
Qiong Nan, Juan Cao, Yongchun Zhu +2
Fake news spread widely on social media in various domains, which lead to real-world threats in many aspects like politics, disasters, and finance. Most existing approaches focus o…