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

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