Entity-Aware Dual Co-Attention Network for Fake News Detection

被引：0

作者：

Yang, Sin-Han ^{[1
]}

Chen, Chung-Chi ^{[2
]}

Huang, Hen-Hsen ^{[3
]}

Chen, Hsin-Hsi ^{[1
]}

机构：

[1] Natl Taiwan Univ, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[2] AIST, Tokyo, Japan

[3] Acad Sinica, Inst Informat Sci, Taipei, Taiwan

来源：

17TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EACL 2023 | 2023年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fake news and misinformation spread rapidly on the Internet. How to identify it and how to interpret the identification results have become important issues. In this paper, we propose a Dual Co-Attention Network (Dual-CAN) for fake news detection, which takes news content, social media replies, and external knowledge into consideration. Our experimental results support that the proposed Dual-CAN outperforms current representative models in two benchmark datasets. We further make in-depth discussions by comparing how models work in both datasets with empirical analysis of attention weights.(1)

引用

页码：106 / 113

页数：8

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