Unveiling Opinion Evolution via Prompting and Diffusion for Short Video Fake News Detection
Linlin Zong, Jiahui Zhou, Wenmin Lin, Xinyue Liu, Xianchao Zhang, Bo Xu
Abstract
Short video fake news detection is crucial for combating the spread of misinformation. Current detection methods tend to aggregate features from individual modalities into multimodal features, overlooking the implicit opinions and the evolving nature of opinions across modalities. In this paper, we mine implicit opinions within short video news and promote the evolution of both explicit and implicit opinions across all modalities. Specifically, we design a prompt template to mine implicit opinions regarding the credibility of news from the textual component of videos. Additionally, we employ a diffusion model that encourages the interplay among diverse modal opinions, including those extracted through our implicit opinion prompts. Experimental results on a publicly available dataset for short video fake news detection demonstrate the superiority of our model over state-of-the-art methods.- Anthology ID:
- 2024.findings-acl.642
- Volume:
- Findings of the Association for Computational Linguistics ACL 2024
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand and virtual meeting
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10817–10826
- Language:
- URL:
- https://aclanthology.org/2024.findings-acl.642
- DOI:
- Cite (ACL):
- Linlin Zong, Jiahui Zhou, Wenmin Lin, Xinyue Liu, Xianchao Zhang, and Bo Xu. 2024. Unveiling Opinion Evolution via Prompting and Diffusion for Short Video Fake News Detection. In Findings of the Association for Computational Linguistics ACL 2024, pages 10817–10826, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.
- Cite (Informal):
- Unveiling Opinion Evolution via Prompting and Diffusion for Short Video Fake News Detection (Zong et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.findings-acl.642.pdf