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

Early Results from COVID-19 Studies (309) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (47) JMIR Theme Issue: COVID-19 Special Issue (2461) Infodemiology and Infoveillance (1369)

Published on in Vol 7 (2023)

This is a member publication of University of Birmingham (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41134, first published .
Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study

Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study

Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study

Authors of this article:

Iris Thiele Isip Tan1 Author Orcid Image ;   Jerome Cleofas2 Author Orcid Image ;   Geoffrey Solano3 Author Orcid Image ;   Jeanne Genevive Pillejera1 Author Orcid Image ;   Jasper Kyle Catapang4 Author Orcid Image
Article Authors Cited by (1) Tweetations (12) Metrics

Journals

  1. Hussna A, Alam M, Islam R, Alkhamees B, Hassan M, Uddin M. Dissecting the infodemic: An in-depth analysis of COVID-19 misinformation detection on X (formerly Twitter) utilizing machine learning and deep learning techniques. Heliyon 2024;10(18):e37760 View