An Emotion-Guided Approach to Domain Adaptive Fake News Detection Using Adversarial Learning (Student Abstract) Article Swipe

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

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1609/aaai.v37i13.26949

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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Computer Science

Fake News

Artificial Intelligence

Mathematical Analysis

Systems Engineering

Philosophy

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Adversarial system Domain (mathematical analysis) Computer science Emotion detection Fake news Task (project management) Feature (linguistics) Artificial intelligence Key (lock) Feature engineering Machine learning Emotion recognition Deep learning Computer security Engineering Internet privacy Mathematics Linguistics Mathematical analysis Systems engineering Philosophy

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Type: article
Language: en
Landing Page: https://doi.org/10.1609/aaai.v37i13.26949
PDF: https://ojs.aaai.org/index.php/AAAI/article/download/26949/26721
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Cited By: 6
References: 9
Related Works: 10
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DOI: https://doi.org/10.1609/aaai.v37i13.26949

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Title: An Emotion-Guided Approach to Domain Adaptive Fake News Detection Using Adversarial Learning (Student Abstract)

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Language: en

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Publication year: 2023

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Publication date: 2023-06-26

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

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Landing page: https://doi.org/10.1609/aaai.v37i13.26949

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Concepts: Adversarial system, Domain (mathematical analysis), Computer science, Emotion detection, Fake news, Task (project management), Feature (linguistics), Artificial intelligence, Key (lock), Feature engineering, Machine learning, Emotion recognition, Deep learning, Computer security, Engineering, Internet privacy, Mathematics, Linguistics, Mathematical analysis, Systems engineering, Philosophy

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Cited by: 6

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