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

Infodemiology and Infoveillance (1349) Early Results from COVID-19 Studies (299) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Public (e)Health, Digital Epidemiology and Public Health Informatics (725) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49300, first published .
Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

Authors of this article:

Jing Dai1 Author Orcid Image ;   Fang Lyu1 Author Orcid Image ;   Lin Yu1 Author Orcid Image ;   Yunyu He2 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Fallatah D, Adekola H. Digital epidemiology: harnessing big data for early detection and monitoring of viral outbreaks. Infection Prevention in Practice 2024;6(3):100382 View
  2. Khorram-Manesh A, Burkle Jr F, Goniewicz K. Pandemics: past, present, and future: multitasking challenges in need of cross-disciplinary, transdisciplinary, and multidisciplinary collaborative solutions. Osong Public Health and Research Perspectives 2024;15(4):267 View