FuDFEND: Fuzzy-Domain for Multi-domain Fake News Detection

Author:

Liang Chaoqi,Zhang Yu,Li Xinyuan,Zhang Jinyu,Yu Yongqi

Publisher

Springer Nature Switzerland

Reference30 articles.

1. Tavernise, S.: As fake news spreads lies, more readers shrug at the truth. The New York Times. Accessed 26 Jan 2017

2. Rawat, M., Kanojia, D.: Automated Evidence Collection for Fake News Detection. arXiv:2112.06507 (2021)

3. Hangloo, S., Arora, B.: Fake news detection tools and methods — a review. Int. J. Adv. Innovat. Res. 8(2) (IX), 100–108 (2021)

4. Mouratidis, D., Nikiforos, M.N., Kermanidis, K.L.: Deep learning for fake news detection in a pairwise textual input schema. Computation 9(2), 20 (2021)

5. Pérez-Rosas, V., Kleinberg, B., Lefevre, A., et al.: Automatic detection of fake news. In: Association for Computational Linguistics, pp. 3391–3401 (2017)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Prompt Learning for Low-Resource Multi-Domain Fake News Detection;2023 International Conference on Asian Language Processing (IALP);2023-11-18

2. KG-MFEND: an efficient knowledge graph-based model for multi-domain fake news detection;The Journal of Supercomputing;2023-05-15

3. Soft-Label for Multi-Domain Fake News Detection;IEEE Access;2023

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