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Few-shot fake news detection via prompt-based tuning
- Source :
- Journal of Intelligent & Fuzzy Systems. :1-10
- Publication Year :
- 2023
- Publisher :
- IOS Press, 2023.
-
Abstract
- As people increasingly use social media to read news, fake news has become a major problem for the public and government. One of the main challenges in fake news detection is how to identify them in the early stage of propagation. Another challenge is that detection model training requires large amounts of labeled data, which are often unavailable or expensive to acquire. To address these challenges, we propose a novel Fake News Detection model based on Prompt Tuning (FNDPT). FNDPT first designs a prompt-based template for early fake news detection. This mechanism incorporates contextual information into textual content and extracts relevant knowledge from pre-trained language models. Furthermore, our model utilizes prompt-based tuning to enhance the performance in a few-shot setting. Experimental results on two real-world datasets verify the effectiveness of FNDPT.
- Subjects :
- Statistics and Probability
Artificial Intelligence
General Engineering
Subjects
Details
- ISSN :
- 18758967 and 10641246
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Accession number :
- edsair.doi...........f56abfe81ed9fd7ef6bfdaaa8a45bd33