This paper is in the following e-collection/theme issue:

Misinformation and Disinformation Outbreaks and Information Prevalence Studies (47) JMIR Theme Issue: COVID-19 Special Issue (2461) Infodemic Management (49) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Natural Language Processing (706)

Published on in Vol 3 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43694, first published .
The Early Detection of Fraudulent COVID-19 Products From Twitter Chatter: Data Set and Baseline Approach Using Anomaly Detection

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

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

Authors of this article:

Abeed Sarker1 Author Orcid Image ;   Sahithi Lakamana1 Author Orcid Image ;   Ruqi Liao2 Author Orcid Image ;   Aamir Abbas3 Author Orcid Image ;   Yuan-Chi Yang1 Author Orcid Image ;   Mohammed Al-Garadi1 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

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