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

Infodemic Management (49) JMIR Theme Issue: COVID-19 Special Issue (2452) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465) Quality/Credibility of eHealth Information and Trust Issues (531)

Published on in Vol 2, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38756, first published .
COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic

COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic

COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic

Authors of this article:

Nikhil Kolluri1 Author Orcid Image ;   Yunong Liu2 Author Orcid Image ;   Dhiraj Murthy3 Author Orcid Image
Article Authors Cited by (9) Tweetations (8) Metrics

Nikhil Kolluri   1 * , BS ;   Yunong Liu   2 * ;   Dhiraj Murthy   3 , BA, MSc, DPhil

1 Computational Media Lab, Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States

2 School of Engineering, College of Science and Engineering, University of Edinburgh, Edinburgh, United Kingdom

3 Computational Media Lab, School of Journalism and Media, Moody College of Communication, The University of Texas at Austin, Austin, TX, United States

*these authors contributed equally

Corresponding Author:

  • Dhiraj Murthy, BA, MSc, DPhil
  • Computational Media Lab
  • School of Journalism and Media, Moody College of Communication
  • The University of Texas at Austin
  • 300 W Dean Keeton (A0900)
  • Austin, TX, 78712
  • United States
  • Phone: 1 512-471-5775
  • Email: Dhiraj.Murthy@austin.utexas.edu