COVIDFakeExplainer: An explainable machine learning based web application for detecting COVID-19 fake news

Dylan Warman, Muhammad Ashad Kabir

Research output: Book chapter/Published conference paperConference paperpeer-review

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Fake news has emerged as a critical global issue, magnified by the COVID-19 pandemic, underscoring the need for effective preventive tools. Leveraging machine learning, including deep learning techniques, offers promise in combatting fake news. This paper goes beyond by establishing BERT as the superior model for fake news detection and demonstrates its utility as a tool to empower the general populace. We have implemented a browser extension, enhanced with explainability features, enabling real-time identification of fake news and delivering easily interpretable explanations. To achieve this, we have employed two publicly available datasets and created seven distinct data configurations to evaluate three prominent machine learning architectures. Our comprehensive experiments affirm BERT's exceptional accuracy in detecting COVID-19-related fake news. Furthermore, we have integrated an explainability component into the BERT model and deployed it as a service through Amazon's cloud API hosting (AWS). We have developed a browser extension that interfaces with the API, allowing users to select and transmit data from web pages, receiving an intelligible classification in return. This paper presents a practical end-to-end solution, highlighting the feasibility of constructing a holistic system for fake news detection, which can significantly benefit society.
Original languageEnglish
Title of host publication10th IEEE Asia-Pacific Conference on Computer Science and Data Engineering
Place of PublicationUnited States
PublisherIEEE Xplore
Number of pages6
ISBN (Electronic)9798350341072
ISBN (Print)9798350341089 (Print on demand)
Publication statusPublished - 2023
Event10th Asia-Pacific Conference on Computer Science and Data Engineering: IEEE CSDE 2023 - Shangir-La’s Fijian Resort, Yanuca Island, Fiji
Duration: 04 Dec 202306 Dec 2023 (Schedule) (Reviewers Guide) (Wayback Machine link to website)


Conference10th Asia-Pacific Conference on Computer Science and Data Engineering
Abbreviated titleSecure Data Via Blockchain
CityYanuca Island
OtherThe 10th IEEE CSDE 2023, the Asia-Pacific Conference on Computer Science and Data Engineering 2023, offers an ideal opportunity for researchers, engineers, academics and students from all over the world to bring the latest technological advances and applications in popular computer science and data engineering areas, as well as to network and promote the discipline. Cutting-edge researchers will present keynote speeches during a three-day program featuring tutorials and technical sessions on theory, analysis, design, testing and advances in computer science, data science and data engineering. Scholarships are offered for students to cover the cost of attending the conference and reduced registration fees apply to delegates from UN least developed countries. The papers presented at the conference will be included in the IEEE Digital Library.

This year IEEE CSDE 2023 is being held at the Shangir-La’s Fijian Resort, Yanuca Island, Nadi, Fiji. Yanuca Island is a leading tourism, business and events city boasting arguably one of the best lifestyles in the world. The island is only 43.13 km far from the Nadi International Airport. Inspiration is on the horizon, and nature is at your doorstep on the private Yanuca Island, Shangri-La Fijian Resort, Yanuca Island, Fiji, offers the essence of an exclusive island hideaway yet is conveniently connected to the mainland by a causeway. The 443 ocean-view guest rooms take their inspiration from a traditional Fijian village featuring rich local culture and nature elements. The Conference is hosted and sponsored by the Computer Society, The University of the South Pacific, Fiji; The University of Fiji, Fiji, CQUniversity, Australia; Massy University, New Zealand and NPS Australia.
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