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

Misinformation and Disinformation Outbreaks and Information Prevalence Studies (93) Theme Issue 2023: Exploring the Intersection Between Health Information, Misinformation, and Generative AI Technologies (10) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Patient Education for Cancer (227) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1911) Cancer Epidemiology, Cancer Surveillance and Infodemiology (113) Natural Language Processing (917) Machine Learning (2074)

Published on in Vol 5 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62703, first published .
Identifying Misinformation About Unproven Cancer Treatments on Social Media Using User-Friendly Linguistic Characteristics: Content Analysis

Identifying Misinformation About Unproven Cancer Treatments on Social Media Using User-Friendly Linguistic Characteristics: Content Analysis

Identifying Misinformation About Unproven Cancer Treatments on Social Media Using User-Friendly Linguistic Characteristics: Content Analysis

Authors of this article:

Ilona Fridman1 Author Orcid Image ;   Dahlia Boyles2 Author Orcid Image ;   Ria Chheda3 Author Orcid Image ;   Carrie Baldwin-SoRelle4 Author Orcid Image ;   Angela B Smith1 Author Orcid Image ;   Jennifer Elston Lafata1, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics Author Video

Journals

  1. Fridman I, Johnson S, Derry-Vick H. When Limited Clinical Time With Patients Meets Unlimited Online Information. JMIR Cancer 2025;11:e79031 View
  2. Gram E, Moynihan R, Copp T, Shih P, Albarqouni L, Akl E, Smith C, Hardiman L, Nickel B. Addressing misleading medical information on social media: a scoping review of current interventions. BMJ Evidence-Based Medicine 2025;30(6):420 View
  3. Wang G, Zhang Y, Wang W, Zhu Y, Lu W, Wang C, Bi H, Yang X. Detection of Medical Misinformation in Hemangioma Patient Education: Comparative Study of ChatGPT-4o and DeepSeek-R1 Large Language Models. JMIR AI 2025;4:e76372 View