Identifying COVID-19 Fake News on Social Networks Using Deep Learning: You will not know what happens next!
Fake News has long been an influential source of information on social media, misleading people and causing unpredictable consequences, especially in the COVID-19 era when the spread of Fake News has been amplified. There is a need to develop a platform that can detect Fake News on social platforms. With the development of Natural Language Processing (NLP) and Deep Learning, the detection of misleading information is becoming a reality. In this paper, we propose a feasible optimization scheme that combines and optimizes NLP and Deep Learning to improve the accuracy of Fake News detection. Our model achieves a hit rate of up to 95.3% compared to state-of-the-art techniques. In the proposed system, a GUI-based interface is also designed and developed to facilitate news detection.
Authors
- Pushpendu Kar (ORCID: https://orcid.org/0000-0003-4410-1172)
- Zhongyi Wang (ORCID: https://orcid.org/0000-0002-8982-2806)
Institutions
- University of Nottingham Ningbo China (CN)
Publication Details
- Journal
- WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS
- Published
- 2024-10-10
- DOI
- https://doi.org/10.37394/23207.2024.21.160
- Citations
- 1
- Primary Topic
- Misinformation and Its Impacts
- Type
- article
- Field-Weighted Citation Impact
- 1.13