Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models
BackgroundDuring the COVID-19 pandemic, the continuous spread of misinformation on the internet posed an ongoing threat to public trust and understanding of epidemic prevention policies. Although the pandemic is now under control, information regarding the risks of long-term...
Saved in:
| Main Authors: | Jian-An Chen, Wu-Chun Chung, Che-Lun Hung, Chun-Ying Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-05-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e73601 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A fuzzy rank-based deep ensemble methodology for multi-class skin cancer classification
by: Arindam Halder, et al.
Published: (2025-02-01) -
Gendered disinformation in Spanish-language fact-checking: origin, methodology, and perspectives
by: Marta Pérez Pereiro, et al.
Published: (2024-09-01) -
Detecting pro-kremlin disinformation using large language models
by: Marianne Kramer, et al.
Published: (2025-06-01) -
Emotional prompting amplifies disinformation generation in AI large language models
by: Rasita Vinay, et al.
Published: (2025-04-01) -
Large language models can consistently generate high-quality content for election disinformation operations.
by: Angus R Williams, et al.
Published: (2025-01-01)