Stemming the Tide of Fake News about the COVID-19 Pandemic

Authors

  • Chih-yuan Li New Jersey Institute of Technology
  • Soon A. Chun College of Staten Island
  • James Geller NJIT

DOI:

https://doi.org/10.32473/flairs.v35i.130716

Keywords:

Fake News Identification, COVID-19, Machine Learning, Sentiment Analysis, Infodemic, Metadata Tags

Abstract

While the world has been combating COVID, there has also been an ongoing “Infodemic,” caused by the spread of fake news about the pandemic. Due to the rapid data sharing on social media, the impact of fake news can be quite damaging. Citizens might mistake fakes news for real news. Human lives have been lost due to fake information about COVID. Our goal is to identify fake news on social media and help stem the spread by deep learning approaches. To understand the different characteristics in fake and real news, we conducted behavioral and sentiment analyses between fake and real news regarding the COVID pandemic. We then further built detection models based on feature elimination, and we identified differences of model robustness based on selected features.

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Published

04-05-2022

How to Cite

Li, C.- yuan, Chun, S., & Geller, J. (2022). Stemming the Tide of Fake News about the COVID-19 Pandemic. The International FLAIRS Conference Proceedings, 35. https://doi.org/10.32473/flairs.v35i.130716

Issue

Vol. 35 (2022): Proceedings of FLAIRS-35

Section

Main Track Proceedings

License

Copyright (c) 2022 Chih-yuan Li, Soon A. Chun, James Geller

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.