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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1481) Artificial Intelligence (1186) Cyberpharmacies (39) Infodemiology and Infoveillance (1269) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Big Data (215) Machine Learning (1370) Natural Language Processing (636) Infectious Diseases (non-STD/STI) (1478) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) Mass Media/Social Media Communication and Campaigns (446) Outbreak and Pandemic Preparedness and Management (1673) Infoveillance and Social Listening (178)

Published on in Vol 6, No 3 (2020): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20794, first published .
Big Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram

Big Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram

Big Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram

Authors of this article:

Tim Ken Mackey1, 2, 3, 4 Author Orcid Image ;   Jiawei Li2, 3, 4 Author Orcid Image ;   Vidya Purushothaman3, 5 Author Orcid Image ;   Matthew Nali1, 3, 4 Author Orcid Image ;   Neal Shah2, 3 Author Orcid Image ;   Cortni Bardier6 Author Orcid Image ;   Mingxiang Cai3, 4 Author Orcid Image ;   Bryan Liang3 Author Orcid Image
Article Authors Cited by (64) Tweetations (80) Metrics

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