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Recent works on fake news detection have shown the efficacy of using emotionsas a feature for improved performance. However, the cross-domain impact ofemotion-guided features for fake news detection still remains an open problem.In this work, we propose an emotion-guided, domain-adaptive, multi-taskapproach for cross-domain fake news detection, proving the efficacy ofemotion-guided models in cross-domain settings for various datasets.

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