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

Infodemiology and Infoveillance (1558) JMIR Theme Issue: COVID-19 Special Issue (2554) Public Health Policy (98)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46589, first published .
Quantifying Health Policy Uncertainty in China Using Newspapers: Text Mining Study

Quantifying Health Policy Uncertainty in China Using Newspapers: Text Mining Study

Quantifying Health Policy Uncertainty in China Using Newspapers: Text Mining Study

Authors of this article:

Chen Chen1, 2 Author Orcid Image ;   Junli Zhu1, 2 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Xu J, Tan X, Quan Y, Gong D, Deng H, Zhao J, Huang X, Zhang Y, Ren Z, Rong Z, Zeng W, Li X, Zheng W, Xiao S, Xiao J, Zhang M, Zheng J. Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. PLOS Neglected Tropical Diseases 2025;19(2):e0012832 View
  2. Chen Q, Crooks A, Sullivan A, Surtees J, Tumiel-Berhalter L, Yang Y. From print to perspective: A mixed-method analysis of the convergence and divergence of COVID-19 topics in newspapers and interviews. PLOS Digital Health 2025;4(2):e0000736 View
  3. Anderson L, Hoyt C, Zucker J, McNaughton A, Teuton J, Karis K, Arokium-Christian N, Warley J, Stromberg Z, Gyori B, Kumar N. Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions. Frontiers in Immunology 2025;16 View

Books/Policy Documents

  1. Kong P, Zheng Q, Mo Z, Hu C. Frontier Computing: Volume 2. View