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

作者

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

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

关键词:

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

摘要

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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已出版

2022-05-04

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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

期

卷 35 (2022): Proceedings of FLAIRS-35

栏目

Main Track Proceedings

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