Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection

Lianwei Wu, Yuan Rao, Haolin Jin, Ambreen Nazir, Ling Sun

Abstract
Recently, neural networks based on multi-task learning have achieved promising performance on fake news detection, which focuses on learning shared features among tasks as complementarity features to serve different tasks. However, in most of the existing approaches, the shared features are completely assigned to different tasks without selection, which may lead to some useless and even adverse features integrated into specific tasks. In this paper, we design a sifted multi-task learning method with a selected sharing layer for fake news detection. The selected sharing layer adopts gate mechanism and attention mechanism to filter and select shared feature flows between tasks. Experiments on two public and widely used competition datasets, i.e. RumourEval and PHEME, demonstrate that our proposed method achieves the state-of-the-art performance and boosts the F1-score by more than 0.87%, 1.31%, respectively.
Anthology ID:
D19-1471
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
4644–4653
Language:
URL:
https://aclanthology.org/D19-1471
DOI:
10.18653/v1/D19-1471
Bibkey:
Cite (ACL):
Lianwei Wu, Yuan Rao, Haolin Jin, Ambreen Nazir, and Ling Sun. 2019. Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4644–4653, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection (Wu et al., EMNLP-IJCNLP 2019)
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https://preview.aclanthology.org/nschneid-patch-3/D19-1471.pdf
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