Developing a Web-Based COVID-19 Fake News Detector With Deep Learning

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Abstract

Fake news and misleading information have been determined as ongoing social challenges in the post-pandemic era. COVID-19-related misinformation has been posted online, which is a crucial impact on society. Despite technological abuses of spreading misinformation, artificial intelligence can help to terminate it. This chapter proposes a cloud-based architecture to detect misleading information on COVID-19-related news and articles. The system has been illustrated through misinformation extraction, fake news detection, and ground-truth testing. A web-based application has been presented with a dashboard-like user interface design using cloud computing. A bench of word embeddings and deep learning algorithms has been investigated for determining the optimal model. The anti-misinformation system can identify fake news in a second with a reliability study operated in a cloud computing environment. Potential limitations and suggestions are also discussed in terms of improving the system for industrial consideration.

Publisher

IGI Global

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