Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30715, first published .
Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach

Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach

Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach

Authors of this article:

Chen Luo1, 2 Author Orcid Image ;   Kaiyuan Ji1 Author Orcid Image ;   Yulong Tang3 Author Orcid Image ;   Zhiyuan Du1 Author Orcid Image

Journals

  1. Ferawati K, Liew K, Aramaki E, Wakamiya S. Monitoring Mentions of COVID-19 Vaccine Side Effects on Japanese and Indonesian Twitter: Infodemiological Study. JMIR Infodemiology 2022;2(2):e39504 View
  2. Simeoni R, Maccioni G, Giansanti D. The Vaccination Process against the COVID-19: Opportunities, Problems and mHealth Support. Healthcare 2021;9(9):1165 View
  3. Luo C, Chen A, Cui B, Liao W. Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China. Telematics and Informatics 2021;65:101712 View
  4. Yin J. Media Data and Vaccine Hesitancy: Scoping Review. JMIR Infodemiology 2022;2(2):e37300 View
  5. Kim M, Noh Y, Yamada A, Hong S. Comparison of the Erectile Dysfunction Drugs Sildenafil and Tadalafil Using Patient Medication Reviews: Topic Modeling Study. JMIR Medical Informatics 2022;10(2):e32689 View
  6. Luo C, Dai R, Deng Y, Chen A. How did Chinese public health authorities promote COVID-19 vaccination on social media? A content analysis of the vaccination promotion posts. DIGITAL HEALTH 2023;9 View
  7. Thampy P, Sharma S, Joshi P, Raj M, Rupani A, Tyagi S, Joshi A. COVID-19 Vaccine Hesitancy Among Healthcare Workers: A Phenomenological Study of Skepticism. Cureus 2024 View
  8. Kim N, Lee N. Structural Topic Modeling Analysis of Patient Safety Interest among Health Consumers in Social Media. Journal of Korean Academy of Nursing 2024;54(2):266 View