Accuracy of a large language model in distinguishing anti- and pro-vaccination messages on social media: The case of human papillomavirus vaccination-Reference-Cited by-同舟云学术

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Accuracy of a large language model in distinguishing anti- and pro-vaccination messages on social media: The case of human papillomavirus vaccination

Published:2024-06 Issue: Volume:42 Page:102723
ISSN:2211-3355
Container-title:Preventive Medicine Reports
language:en
Short-container-title:Preventive Medicine Reports

Author:

Kim Soojong^ORCID,Kim Kwanho,Wonjeong Jo Claire

Publisher

Elsevier BV

Reference25 articles.

1. Cross-platform social dynamics: an analysis of ChatGPT and COVID-19 vaccine conversations;Alipour;Sci Rep.,2024

2. Analyzing Social-Cyber Maneuvers for Spreading COVID-19 Pro- and Anti- Vaccine Information;Blane,202357

3. Brown TB, Mann B, Ryder N, et al. Language Models are Few-Shot Learners. Published online July 22, 2020. Accessed September 4, 2023. http://arxiv.org/abs/2005.14165.

4. Where We Go From Here: Health Misinformation on Social Media;Chou;Am J Public Health.,2020

5. Social Media Use in the United States: Implications for Health Communication;Chou;Journal of Medical Internet Research.,2009

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1. Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions;BMC Medicine;2024-09-02

2. Multitask Learning for Crash Analysis: A Fine-Tuned LLM Framework Using Twitter Data;Smart Cities;2024-09-01

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