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.
@article{arxiv.2302.03475,
title = {Entity-Aware Dual Co-Attention Network for Fake News Detection},
author = {Sin-Han Yang and Chung-Chi Chen and Hen-Hsen Huang and Hsin-Hsi Chen},
journal= {arXiv preprint arXiv:2302.03475},
year = {2023}
}