Exploring public emotions on obesity during the COVID-19 pandemic using sentiment analysis and topic modeling : cross-sectional study
ContributorsCorreia, Jorge
; Ahmad, Sarmad Shaharyar
; Waqas, Ahmed
; Meraj, Hafsa
; Pataky, Zoltan
Published inJMIR. Journal of medical internet research, vol. 26, e52142
Publication date2024-10-11
First online date2024-10-11
Abstract
Keywords
- BERT
- Bidirectional Encoder Representations from Transformers
- NLP
- Attitude
- Celebrities
- General public
- Infodemic
- Natural language processing
- Obese
- Obesity
- Opinion
- Overweight
- Perception
- Perspective
- Sentiment
- Social media
- Topic modeling
- Tweet
- Weight
Affiliation entities
Citation (ISO format)
CORREIA, Jorge et al. Exploring public emotions on obesity during the COVID-19 pandemic using sentiment analysis and topic modeling : cross-sectional study. In: JMIR. Journal of medical internet research, 2024, vol. 26, p. e52142. doi: 10.2196/52142
Main files (1)
Article (Published version)
Secondary files (4)
Identifiers
- PID : unige:181109
- DOI : 10.2196/52142
- PMID : 39393064
- PMCID : PMC11512131
Additional URL for this publicationhttps://www.jmir.org/2024/1/e52142
Journal ISSN1438-8871
