Identifying COVID-19 Fake News on Social Networks Using Deep Learning: You will not know what happens next!
Year: 2024
Type: article
Abstract: 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, Zhongyi Wang
Institution: University of Nottingham Ningbo China
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4403283136