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

Infodemiology and Infoveillance (1558) Public (e)Health, Digital Epidemiology and Public Health Informatics (1008) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Artificial Intelligence (2129) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1911) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (93)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44356, first published .
Tweeting for Health Using Real-time Mining and Artificial Intelligence–Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter

Tweeting for Health Using Real-time Mining and Artificial Intelligence–Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter

Tweeting for Health Using Real-time Mining and Artificial Intelligence–Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter

Authors of this article:

Plinio Pelegrini Morita1, 2, 3, 4, 5 Author Orcid Image ;   Irfhana Zakir Hussain1, 6 Author Orcid Image ;   Jasleen Kaur1 Author Orcid Image ;   Matheus Lotto1, 7 Author Orcid Image ;   Zahid Ahmad Butt1 Author Orcid Image
Article Authors Cited by (13) Tweetations (7) Metrics

Journals

  1. Lotto M, Zakir Hussain I, Kaur J, Butt Z, Cruvinel T, Morita P. Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study. Journal of Medical Internet Research 2023;25:e44586 View
  2. Ramírez-Gutiérrez A, Solano García P, Morales Matamoros O, Moreno Escobar J, Tejeida-Padilla R. Systems Approach for the Adoption of New Technologies in Enterprises. Systems 2023;11(10):494 View
  3. Zhu Y, Zhang R, Yin S, Sun Y, Womer F, Liu R, Zeng S, Zhang X, Wang F. Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation. JMIR Public Health and Surveillance 2024;10:e47428 View
  4. Bishal M, Chowdory M, Das A, Kabir M. COVIDHealth: A novel labeled dataset and machine learning-based web application for classifying COVID-19 discourses on Twitter. Heliyon 2024;10(14):e34103 View
  5. Baxter P, Li M, Wei J, Koizumi N. Public Versus Academic Discourse on ChatGPT in Health Care: Mixed Methods Study. JMIR Infodemiology 2025;5:e64509 View
  6. Padalko H, Chumachenko D, Kaur N, Hussain I, Kaur J, Lotto M, Butt Z, Morita P. Investigation of machine learning approaches to classify war-related content during Russian full-scale invasion of Ukraine. Social Network Analysis and Mining 2025;15(1) View
  7. Padawe D, Takate V, Surve K. Digital Dilemma: The Intersection of Social Media Influencers and Pediatric Dental Health. Journal of Clinical Insights and Research in Dentistry 2025;1(2):82 View
  8. Requena-Mullor J, Garau E, Quintas-Soriano C, López-Rodríguez M, Castro A. An inverse reinforcement learning approach to model health-related information popularity on X (Twitter). Computing 2025;107(10) View
  9. Dewi R, Nugroho A. Sentiment as Signal: Detecting Political Misinformation in Indonesia’s 2024 Election via Lexicon Based NLP. Digitus : Journal of Computer Science Applications 2024;2(3):185 View
  10. Feng X, Luo J, Yang Y, El Baz D, Shi L. Health Misinformation Detection: Approaches, Challenges and Opportunities. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2025;62 View
  11. Boudreault J, Lamothe F, Campagna C, Chebana F. Machine learning for modelling the health impacts of extreme heat: A comprehensive literature review. Environment International 2025;206:109965 View

Conference Proceedings

  1. Hussain I, Kaur J, Lotto M, Butt Z, Morita P. 2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). Design & Development of Misinformation Analysis System for Government Prevention of Public Health Crises View
  2. Hu Y. 2024 3rd International Conference for Innovation in Technology (INOCON). Research on Human Activity Recognition Algorithm Based on Metric Learning View