Understanding Citizens' Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI.
- DOI
- 10.2196/63824
- Published
- 2025 Feb 11
- Container
- Journal of medical Internet research
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.2196/63824,
title = {Understanding Citizens' Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI.},
author = {Saito R and Tsugawa S},
year = {2025},
journal = {Journal of medical Internet research},
doi = {10.2196/63824},
url = {https://doi.org/10.2196/63824}
}RIS
TY - JOUR TI - Understanding Citizens' Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI. AU - Saito R AU - Tsugawa S PY - 2025 JO - Journal of medical Internet research DO - 10.2196/63824 UR - https://doi.org/10.2196/63824 ER -
APA
R, S., & S, T. (2025). Understanding Citizens' Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI.. Journal of medical Internet research. https://doi.org/10.2196/63824
Source records
- pubmed · retrieved 2026-09-25T13:26:50.569Z