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

Infodemiology and Infoveillance (1008) Peer-to-Peer Support and Online Communities (463) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1276) Machine Learning (1009) Mass Media/Social Media Communication and Campaigns (401) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (825) Substance Abuse (272) Opioid and Related Substance Abuse Crisis (69) Infoveillance and Social Listening (135)

Published on in Vol 23 , No 12 (2021) :December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30753, first published .
Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach

Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach

Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach

Authors of this article:

Mai ElSherief 1 Author Orcid Image ;   Steven A Sumner 2 Author Orcid Image ;   Christopher M Jones 3 Author Orcid Image ;   Royal K Law 4 Author Orcid Image ;   Akadia Kacha-Ochana 2 Author Orcid Image ;   Lyna Shieber 5 Author Orcid Image ;   LeShaundra Cordier 5 Author Orcid Image ;   Kelly Holton 3 Author Orcid Image ;   Munmun De Choudhury 6 Author Orcid Image
Article Authors Cited by (3) Tweetations (10) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.