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

Infodemic Management (49) JMIR Theme Issue: COVID-19 Special Issue (2461) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Infodemiology and Infoveillance (1369) Vaccination and Immunization in the Digital Age (378) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Information Quality in Digital Media (347) Quality/Credibility of eHealth Information and Trust Issues (544) Infoveillance and Social Listening (214)

Published on in Vol 2, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37077, first published .
The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model

The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model

The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model

Authors of this article:

Vipin Saini1 Author Orcid Image ;   Li-Lin Liang2, 3, 4, 5 Author Orcid Image ;   Yu-Chen Yang1 Author Orcid Image ;   Huong Mai Le3 Author Orcid Image ;   Chun-Ying Wu4, 5, 6 Author Orcid Image
Article Authors Cited by (4) Tweetations (7) Metrics

Journals

  1. Trzebinski W, Gaczek P, Marciniak B. Is it better to communicate product information abstractly or concretely? The role of consumer product expertise and shopping-stage mindset. Journal of Product & Brand Management 2023;32(2):273 View
  2. Zhao S, Hu S, Zhou X, Song S, Wang Q, Zheng H, Zhang Y, Hou Z. The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review. JMIR Public Health and Surveillance 2023;9:e40201 View
  3. Luo H, Meng X, Zhao Y, Cai M. Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China. Computers in Human Behavior 2023;144:107733 View
  4. Borghouts J, Huang Y, Hopfer S, Li C, Mark G. Wording Matters: The Effect of Linguistic Characteristics and Political Ideology on Resharing of COVID-19 Vaccine Tweets. ACM Transactions on Computer-Human Interaction 2024;31(4):1 View