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arXiv · 2211.13718

Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation

Arjun Choudhry·Inder Khatri·Arkajyoti Chakraborty·Dinesh Kumar Vishwakarma·Mukesh Prasad
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Abstract

Recent works on fake news detection have shown the efficacy of using emotions as a feature or emotions-based features for improved performance. However, the impact of these emotion-guided features for fake news detection in cross-domain settings, where we face the problem of domain shift, is still largely unexplored. In this work, we evaluate the impact of emotion-guided features for cross-domain fake news detection, and further propose an emotion-guided, domain-adaptive approach using adversarial learning. We prove the efficacy of emotion-guided models in cross-domain settings for various combinations of source and target datasets from FakeNewsAMT, Celeb, Politifact and Gossipcop datasets.

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Arjun Choudhry, Inder Khatri, Arkajyoti Chakraborty, Dinesh Kumar Vishwakarma, Mukesh Prasad. 2022-11-24. Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation. https://arxiv.org/abs/2211.13718

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