Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45069, first published .
Topics in Antivax and Provax Discourse: Yearlong Synoptic Study of COVID-19 Vaccine Tweets

Topics in Antivax and Provax Discourse: Yearlong Synoptic Study of COVID-19 Vaccine Tweets

Topics in Antivax and Provax Discourse: Yearlong Synoptic Study of COVID-19 Vaccine Tweets

Journals

  1. Zhou X, Song S, Zhang Y, Hou Z. Deep Learning Analysis of COVID-19 Vaccine Hesitancy and Confidence Expressed on Twitter in 6 High-Income Countries: Longitudinal Observational Study. Journal of Medical Internet Research 2023;25:e49753 View
  2. Bergenfeld I. What can public health communicators learn from Reddit? A perspective for the next pandemic. Frontiers in Public Health 2024;12 View
  3. Lee Y, Alostad H, Davulcu H. Quantifying Variations in Controversial Discussions within Kuwaiti Social Networks. Big Data and Cognitive Computing 2024;8(6):60 View
  4. Xie J, Zhang Z, Zeng S, Hilliard J, An G, Tang X, Jiang L, Yu Y, Wan X, Xu D. Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis. Journal of Medical Internet Research 2025;27:e63190 View

Books/Policy Documents

  1. Breeze R. Reference Module in Social Sciences. View

Conference Proceedings

  1. Hariscandra T, Utami S, Hidayanto A. 2023 Eighth International Conference on Informatics and Computing (ICIC). Exploring COVID-19 Vaccine Hesitancy Through Topic Modeling: A Systematic Literature Review View