Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52142, first published .
Exploring Public Emotions on Obesity During the COVID-19 Pandemic Using Sentiment Analysis and Topic Modeling: Cross-Sectional Study

Exploring Public Emotions on Obesity During the COVID-19 Pandemic Using Sentiment Analysis and Topic Modeling: Cross-Sectional Study

Exploring Public Emotions on Obesity During the COVID-19 Pandemic Using Sentiment Analysis and Topic Modeling: Cross-Sectional Study

Journals

  1. Yu X, Huang H, Lin K, Wang H, Zheng S, Ran X, Liu Y, Wu H, Nashwan A. Exploring the Determinants of Patient Experiences Using the Digital Topic Modeling Approach. Journal of Nursing Management 2025;2025(1) View
  2. Chen A, Dunn L, Fan W, Agrawal N. Audience Responses to Online Public Shaming in Online Environments: Mixed Methods Study. Journal of Medical Internet Research 2025;27:e67923 View
  3. Yang F, Huang X, Huang W, Jiang T. Development and testing of a public health emergency intelligence analysis system based on text analysis and NLP analysis. Frontiers in Public Health 2025;13 View
  4. Bhasker A, Girkar S, Jain V, Lathia T, Selvan C, Shaikh S. The Burden from Within—An Indian Pilot Study on Weight Bias Internalization. Obesity Surgery 2025 View

Conference Proceedings

  1. Lu F, Leng Y. 2025 6th International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation (IoTAIMA). A Multi-stage Text Sentiment Analysis Model View