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The Early Detection of Fraudulent COVID-19 Products From Twitter Chatter: Data Set and Baseline Approach Using Anomaly Detection.

Abeed SarkerSahithi LakamanaRuqi LiaoAamir AbbasYuan-Chi YangMohammed Ali Al-Garadi
Published in: JMIR infodemiology (2023)
Our proposed method is simple, effective, easy to deploy, and does not require high-performance computing machinery unlike deep neural network-based methods. The method can be easily extended to other types of signal detection from social media data. The data set may be used for future research and the development of more advanced methods.
Keyphrases
  • social media
  • neural network
  • electronic health record
  • big data
  • health information
  • sars cov
  • coronavirus disease
  • current status
  • label free
  • machine learning
  • deep learning