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

• URL: http://arxiv.org/abs/2211.17108v1
• Date: Sat, 26 Nov 2022 05:12:07 GMT
• Title: An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning
• Authors: Arkajyoti Chakraborty, Inder Khatri, Arjun Choudhry, Pankaj Gupta, Dinesh Kumar Vishwakarma, Mukesh Prasad
• Abstract summary: We propose an emotion-guided, domain-adaptive, multi-task approach for cross-domain fake news detection. We prove the efficacy of emotion-guided models in cross-domain settings for various datasets.
• Score: 25.438870532556354
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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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