A systematic review of multimodal fake news detection on social media using deep learning models
Universiti Teknologi Petronas · UCSI University · +3 more institutions
Abstract
The volume of data circulating from online sources is growing rapidly and comprises both reliable and unreliable information published through many different sources. Researchers are making plausible efforts to develop reliable methods for detecting and eliminating fake web news. Deep learning (DL) methods play a vital role in addressing various fake news detection problems and are found to perform better compared to conventional approaches, making them state-of-the-art in this field. This paper provides a comprehensive review and analysis of existent DL-based models for multimodal fake news detection, focusing on diverse aspects, including user profiles, news content, images, videos, and audio data. This…
Citation impact
- FWCI
- 140.34
- Percentile
- 100%
- References
- 159
Authors
7Topics & keywords
- Social media
- Fake news
- Deep learning
- Computer science
- Data science
- Artificial intelligence
- Internet privacy
- World Wide Web