Published on in Vol 2, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41198, first published .
Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster–Based BERT Topic Modeling Approach

Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster–Based BERT Topic Modeling Approach

Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster–Based BERT Topic Modeling Approach

Journals

  1. Shankar K, Chandrasekaran R, Jeripity Venkata P, Miketinas D. Investigating the Role of Nutrition in Enhancing Immunity During the COVID-19 Pandemic: Twitter Text-Mining Analysis. Journal of Medical Internet Research 2023;25:e47328 View
  2. Isip Tan I, Cleofas J, Solano G, Pillejera J, Catapang J. Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study. JMIR Formative Research 2023;7:e41134 View
  3. Rao V, Valdez D, Muralidharan R, Agley J, Eddens K, Dendukuri A, Panth V, Parker M. Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2024;26:e57885 View
  4. Nakanishi A, Ichikawa M, Sano Y. Public Discourse Toward Older Drivers in Japan: Longitudinal Analysis of Social Media Data from 2010 to 2022 (Preprint). JMIR Infodemiology 2024 View

Books/Policy Documents

  1. Hayat F, Shatnawi S, Haig E. Technology Enhanced Learning for Inclusive and Equitable Quality Education. View

Conference Proceedings

  1. Lei L, Liu G. 2023 10th International Conference on Behavioural and Social Computing (BESC). Public Perception Towards Intelligent Medical Technologies During and Post COVID-19 Pandemic: Exploring Health Communication in Social Media using Neural Topic Models View