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

Infodemiology and Infoveillance (1436) Public (e)Health, Digital Epidemiology and Public Health Informatics (841) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1082) Artificial Intelligence (1655) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1763) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (61)

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 (6) 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