An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning

Chakraborty, Arkajyoti, Khatri, Inder, Choudhry, Arjun, Gupta, Pankaj, Vishwakarma, Dinesh Kumar, Prasad, Mukesh

arXiv.org Artificial Intelligence 

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.

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