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

Infodemic Management (34) JMIR Theme Issue: COVID-19 Special Issue (2169) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (865) Infodemiology and Infoveillance (1049) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1361) Vaccination and Immunization in the Digital Age (279) Machine Learning (1056)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34231, first published .
The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding

The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding

The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding

Authors of this article:

Loni Hagen 1 Author Orcid Image ;   Ashley Fox 2 Author Orcid Image ;   Heather O'Leary 3 Author Orcid Image ;   DeAndre Dyson 1 Author Orcid Image ;   Kimberly Walker 4 Author Orcid Image ;   Cecile A Lengacher 5 Author Orcid Image ;   Raquel Hernandez 6 Author Orcid Image
Article Authors Cited by (1) Tweetations (18) Metrics

Journals

  1. Zang S, Zhang X, Xing Y, Chen J, Lin L, Hou Z. Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review. Journal of Medical Internet Research 2023;25:e40057 View