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Deep learning analysis of trajectories and spatial variations in HPV vaccine discussions on Chinese Weibo – Communications Medicine
Abstract
Background
Since 2020 China has piloted free human papillomavirus (HPV) vaccinations to address low coverage. We aim to assess the public perceptions, perceived barriers and facilitators towards HPV vaccination in real time, utilizing deep learning-driven social media listening.
Methods
We collected all HPV vaccination discussions on Weibo, a popular Chinese social media platform, made from 2018 to 2023. We annotated 6600 randomly sampled posts manually against behavior change theories, and iteratively fine-tuned and trained deep learning models to auto-annotate all collected posts. Temporal and geographic analyses were conducted regarding public attitudes towards HPV vaccination and their determinants.
Results
Among 1,972,495 posts identified as relevant to HPV vaccines, deep learning models achieve a predictive accuracy of 0.78 to 0.96. 66.6% and 6.1% of posts contain positive and negative attitudes, respectively. The prevalence of positive attitudes increases from 15.8% to 79.1% (P = 3.02×10−11), negative attitudes decline from a peak of 20.3% to 5.5% (P = 1.28×10−5), and misinformation declines from 36.6% to 10.7% (P = 1.33×10−6). Central regions of China exhibit a higher prevalence of positive attitudes, whereas Beijing, Shanghai and northeastern regions show higher prevalence of negative attitudes and misinformation. Positive attitudes are significantly lower for 2-valent vaccines (65.7%) than 4-valent (79.6%; P = 0.0005) or 9-valent vaccines (74.1%; P = 0.0005).
Conclusions
Social media listening represents a promising and economically feasible surveillance approach for timely monitoring of public perceptions of vaccination and a potential tool for policymakers to understand public response to policy adaptation.
Plain Language Summary
The HPV (Human Papillomavirus) vaccination can reduce the chances of getting cervical and some other cancers by reducing the likelihood of being infected with HPV. HPV vaccination rates in China remain low despite government efforts to expand access. Understanding public perceptions of HPV vaccines can help guide strategies for improving vaccination coverage. We analyzed nearly two million posts about HPV vaccines on Weibo, a popular Chinese social media platform, from 2018 to 2023. We used a type of AI, called deep learning algorithms, to classify posts by attitudes towards vaccination, health beliefs, exposures to misinformation, and practical barriers to getting vaccinated. We found that positive attitudes increased substantially over time, while negative attitudes and misinformation declined. However, concerns about vaccine accessibility remained common, and some regions and vaccine types showed higher levels of negative attitudes. These findings suggest that social media monitoring using artificial intelligence can help policymakers track public opinions in real time and inform development of targeted strategies to improve vaccination uptake.
Acknowledgements
The computations in this research were performed using the CFFF platform of Fudan University.
Funding
This work is supported in part by a research grant from Investigator-Initiated Studies Program (No. 61185) of MSD. L.L. is supported by the AIR@InnoHK administered by the Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region. The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. The opinions expressed in this paper are those of the authors and do not necessarily represent those of MSD.
Ethics declarations
Competing interests
Zhiyuan Hou received funding from Merck Investigator Initiated Studies (61185). Leesa Lin is part of the research group from the Vaccine Confidence ProjectTM at LSHTM, which, during the same period of the study, received research grants from GlaxoSmithKline, Merck, and Meta. The other authors declare no competing interests.
Consent to publish
Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
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Wang, Y., Yang, H., Ding, Z. et al. Deep learning analysis of trajectories and spatial variations in HPV vaccine discussions on Chinese Weibo. Commun Med (2026). https://doi.org/10.1038/s43856-026-01720-5
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DOI: https://doi.org/10.1038/s43856-026-01720-5
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