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

Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465) HPV Vaccination (55) Vaccination and Immunization in the Digital Age (374) Mass Media/Social Media Communication and Campaigns (461) Natural Language Processing (693) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (44)

Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26478, first published .
Using Machine Learning–Based Approaches for the Detection and Classification of Human Papillomavirus Vaccine Misinformation: Infodemiology Study of Reddit Discussions

Using Machine Learning–Based Approaches for the Detection and Classification of Human Papillomavirus Vaccine Misinformation: Infodemiology Study of Reddit Discussions

Using Machine Learning–Based Approaches for the Detection and Classification of Human Papillomavirus Vaccine Misinformation: Infodemiology Study of Reddit Discussions

Authors of this article:

Jingcheng Du1 Author Orcid Image ;   Sharice Preston2 Author Orcid Image ;   Hanxiao Sun1, 2 Author Orcid Image ;   Ross Shegog2 Author Orcid Image ;   Rachel Cunningham3 Author Orcid Image ;   Julie Boom3, 4 Author Orcid Image ;   Lara Savas2 Author Orcid Image ;   Muhammad Amith1 Author Orcid Image ;   Cui Tao1 Author Orcid Image
Article Authors Cited by (12) Tweetations (7) Metrics

Journals

  1. Kabir M. Topic and sentiment analysis of responses to Muslim clerics’ misinformation correction about COVID-19 vaccine: Comparison of three machine learning models. Online Media and Global Communication 2022;1(3):497 View
  2. Le D, Kim H, Wen K, Juon H. Disparities in awareness of the HPV vaccine and HPV-associated cancers among racial/ethnic minority populations: 2018 HINTS. Ethnicity & Health 2023;28(4):586 View
  3. Gozuacik N, Sakar C, Ozcan S. Technological forecasting based on estimation of word embedding matrix using LSTM networks. Technological Forecasting and Social Change 2023;191:122520 View
  4. Duzen Z, Riveni M, Aktas M. Analyzing the Spread of Misinformation on Social Networks: A Process and Software Architecture for Detection and Analysis. Computers 2023;12(11):232 View
  5. Yee A. Machine learning, misinformation, and citizen science. European Journal for Philosophy of Science 2023;13(4) View
  6. Zhang B, Naderi N, Mishra R, Teodoro D. Online Health Search Via Multidimensional Information Quality Assessment Based on Deep Language Models: Algorithm Development and Validation. JMIR AI 2024;3:e42630 View
  7. Ashok G, Basu S, Priyamvada P, Anbarasu A, Chintala S, Ramaiah S. Coinfections in human papillomavirus associated cancers and prophylactic recommendations. Reviews in Medical Virology 2024;34(2) View
  8. Kanthi K, Shashi M, Madhuri K. Improved detection of fake news using combined semantic analysis and a source credibility evaluation. i-manager's Journal on Computer Science 2024;12(1):9 View
  9. Rai S, Kornides M, Morgan J, Kumar A, Cappella J, Guntuku S. Detecting and monitoring concerns against HPV vaccination on social media using large language models. Scientific Reports 2024;14(1) View
  10. Murdock I, Carley K, Yağan O. An agent-based model of cross-platform information diffusion and moderation. Social Network Analysis and Mining 2024;14(1) View

Books/Policy Documents

  1. Mohan Kumar A, Jnanavi , Bhat H. Proceedings of the International Conference on Cognitive and Intelligent Computing. View