Identifying COVID-19 Fake News on Social Networks Using Deep Learning: You will not know what happens next!

Pushpendu Kar, Zhongyi Wang

Research output: Journal PublicationArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1973-1987
Number of pages15
JournalWSEAS Transactions on Business and Economics
Volume21
DOIs
Publication statusPublished - 2024

Keywords

  • Covid-19
  • Deep Learning
  • Fake News
  • NLP

ASJC Scopus subject areas

  • Economics and Econometrics
  • Strategy and Management
  • Organizational Behavior and Human Resource Management
  • Marketing

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