An Emotion-Based Multi-Task Approach to Fake News Detection (Student Abstract)
Keywords:Fake News Detection, Rumor Detection, Emotion Classification, Multi-task Learning, Deep Learning
AbstractSocial media, blogs, and online articles are instant sources of news for internet users globally. But due to their unmoderated nature, a significant percentage of these texts are fake news or rumors. Their deceptive nature and ability to propagate instantly can have an adverse effect on society. In this work, we hypothesize that legitimacy of news has a correlation with its emotion, and propose a multi-task framework predicting both the emotion and legitimacy of news. Experimental results verify that our multi-task models outperform their single-task counterparts in terms of accuracy.
How to Cite
Choudhry, A., Khatri, I., & Jain, M. (2022). An Emotion-Based Multi-Task Approach to Fake News Detection (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12929-12930. https://doi.org/10.1609/aaai.v36i11.21601
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