Predicting User Engagement in Health Misinformation Correction on Social Media Platforms in Taiwan: Content Analysis and Text Mining Study
BackgroundHealth misinformation undermines responses to health crises, with social media amplifying the issue. Although organizations work to correct misinformation, challenges persist due to reasons such as the difficulty of effectively sharing corrections and information be...
Saved in:
Main Authors: | Hsin-Yu Kuo, Su-Yen Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2025-01-01
|
Series: | Journal of Medical Internet Research |
Online Access: | https://www.jmir.org/2025/1/e65631 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts
by: Soonchan Kwon, et al.
Published: (2025-01-01) -
Charming e-cigarette users with distorted science: a survey examining social media platform use, nicotine-related misinformation and attitudes towards the tobacco industry
by: Elexis C Kierstead, et al.
Published: (2022-06-01) -
Differential impact from individual versus collective misinformation tagging on the diversity of Twitter (X) information engagement and mobility
by: Junsol Kim, et al.
Published: (2025-01-01) -
The COVID-19 Infodemic: Misinformation About Health on Social Media in Istanbul
by: Serdar Tunçer, et al.
Published: (2022-06-01) -
Text mining social media for competitive analysis
by: Germán Gémar, et al.
Published: (2015-01-01)