Sin-han Yang


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Entity-Aware Dual Co-Attention Network for Fake News Detection
Sin-han Yang | Chung-chi Chen | Hen-Hsen Huang | Hsin-Hsi Chen
Findings of the Association for Computational Linguistics: EACL 2023

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.