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

Artificial Intelligence (1628) Infodemiology and Infoveillance (1433) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (401) Outbreak and Pandemic Preparedness and Management (1775) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1079) Natural Language Processing (770) Generative Language Models Including ChatGPT (438) Theme Issue 2022: Social Media, Ethics, and COVID-19 Misinformation (45) Social Media in Public Health informatics (49)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63824, first published .
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

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

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

Authors of this article:

Ryuichi Saito1 Author Orcid Image ;   Sho Tsugawa1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

There are no citations yet available for this article according to Crossref .