Recent works on fake news detection have shown the efficacy of using emotions as a feature for improved performance. However, the cross-domain impact of emotion-guided features for fake news detection still remains an open problem. In this work, we propose an emotion-guided, domain-adaptive, multi-task approach for cross-domain fake news detection, proving the efficacy of emotion-guided models in cross-domain settings for various datasets.
@article{arxiv.2211.17108,
title = {An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning},
author = {Arkajyoti Chakraborty and Inder Khatri and Arjun Choudhry and Pankaj Gupta and Dinesh Kumar Vishwakarma and Mukesh Prasad},
journal= {arXiv preprint arXiv:2211.17108},
year = {2022}
}
Comments
Accepted in the Student Abstract & Poster Presentation track at AAAI 2023. arXiv admin note: substantial text overlap with arXiv:2211.13718