An Emotion-Guided Approach to Domain Adaptive Fake News Detection Using Adversarial Learning (Student Abstract)
Keywords:Fake News Detection, Domain Adaptation, Adversarial Learning, Emotion Classification, Text Classification, Cross-domain Analysis
AbstractRecent 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.
How to Cite
Chakraborty, A., Khatri, I., Choudhry, A., Gupta, P., Vishwakarma, D. K., & Prasad, M. (2023). An Emotion-Guided Approach to Domain Adaptive Fake News Detection Using Adversarial Learning (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16178-16179. https://doi.org/10.1609/aaai.v37i13.26949
AAAI Student Abstract and Poster Program