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Proceedings of the AAAI Conference on Artificial Intelligence

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Detecting Fake News in Short Videos Through Multi-View Ag...
Nuo Li, Yuan · 2026-03-14 · via Proceedings of the AAAI Conference on Artificial Intelligence

Authors

  • Nuo Li School of Automation, Nanjing University of Information Science and Technology School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University
  • Yuan Xiong School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University
  • Chengliang Liu Laboratory for Artificial Intelligence in Design, The Hong Kong Polytechnic University
  • Jie Wen School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen
  • Chao Huang School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University

DOI:

https://doi.org/10.1609/aaai.v40i1.37028

Abstract

The increasing prominence of short video platforms has positioned them as a primary channel for public awareness of current events, while also facilitating the widespread dissemination of fake news, thus highlighting the critical need for automated detection technologies. In contrast to fake news confined to text and images, short video news encompasses multiple modalities and extensive information, presenting heightened challenges. Most existing research emphasizes the analysis of news content or user comments alone, while overlooking the crucial role of publishers, leading to poor model performance when handling fake news lacking obvious false signals. Therefore, we propose a Publisher Profiling Module to identify new false signals. To enable a more comprehensive detection of misinformation, we design a Multi-View Aggregation (MVA) model, simultaneously evaluating news from three distinct perspectives: sentiment analysis, content understanding, and publisher profiling. Late fusion is applied at the decision level to leverage the complementary strengths of these perspectives, addressing the limitations of single-view methods. Our experiments conducted on the FakeSV and FVC datasets demonstrate the superior performance of the proposed method.

How to Cite

Li, N., Xiong, Y., Liu, C., Wen, J., & Huang, C. (2026). Detecting Fake News in Short Videos Through Multi-View Aggregation. Proceedings of the AAAI Conference on Artificial Intelligence, 40(1), 632–640. https://doi.org/10.1609/aaai.v40i1.37028

Issue

Section

AAAI Technical Track on Application Domains I

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