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

Infodemiology and Infoveillance (1360) Peer-to-Peer Support and Online Communities (644) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1656) Machine Learning (1486) Mass Media/Social Media Communication and Campaigns (466) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1048) Substance Abuse (426) Opioid and Related Substance Misuse (149) Infoveillance and Social Listening (211)

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 ElSherief1 Author Orcid Image ;   Steven A Sumner2 Author Orcid Image ;   Christopher M Jones3 Author Orcid Image ;   Royal K Law4 Author Orcid Image ;   Akadia Kacha-Ochana2 Author Orcid Image ;   Lyna Shieber5 Author Orcid Image ;   LeShaundra Cordier5 Author Orcid Image ;   Kelly Holton3 Author Orcid Image ;   Munmun De Choudhury6 Author Orcid Image
Article Authors Cited by (8) Tweetations (6) Metrics

Journals

  1. Alibudbud R, Cleofas J. Global utilization of online information for substance use disorder: An infodemiological study of Google and Wikipedia from 2004 to 2022. Journal of Nursing Scholarship 2023;55(3):665 View
  2. Garcia G, Dehghanpoor R, Stringfellow E, Gupta M, Rochelle J, Mason E, Pujol T, Jalali M. Identifying and Characterizing Medical Advice-Seekers on a Social Media Forum for Buprenorphine Use. International Journal of Environmental Research and Public Health 2022;19(10):6281 View
  3. ElSherief M, Sumner S, Krishnasamy V, Jones C, Law R, Kacha-Ochana A, Schieber L, De Choudhury M. Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study. JMIR Formative Research 2024;8:e44726 View
  4. Chi Y, Chen H. Investigating Substance Use via Reddit: Systematic Scoping Review. Journal of Medical Internet Research 2023;25:e48905 View
  5. Yuan Y, Kasson E, Taylor J, Cavazos-Rehg P, De Choudhury M, Aledavood T. Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach. JMIR Formative Research 2024;8:e54433 View
  6. O'Kelly B, Holmes P, Cheng A, Lee J, Tofighi B. Dissemination of health content through social networks: YouTube and opioid use disorders. Journal of Substance Use and Addiction Treatment 2024;165:209475 View
  7. Almeida A, Patton T, Conway M, Gupta A, Strathdee S, Bórquez A. The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review. JMIR Infodemiology 2024;4:e51156 View

Books/Policy Documents

  1. Pendyala V. Deep Learning Research Applications for Natural Language Processing. View