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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jul 28, 2021
Date Accepted: Dec 3, 2021
Date Submitted to PubMed: Dec 8, 2021

The final, peer-reviewed published version of this preprint can be found here:

The Evolution and Disparities of Online Attitudes Toward COVID-19 Vaccines: Year-long Longitudinal and Cross-sectional Study

Zhang C, Xu S, Li Z, Liu G, Dai D, Dong C

The Evolution and Disparities of Online Attitudes Toward COVID-19 Vaccines: Year-long Longitudinal and Cross-sectional Study

J Med Internet Res 2022;24(1):e32394

DOI: 10.2196/32394

PMID: 34878410

PMCID: 8786033

Evolutions and Disparities of Online Attitudes Towards COVID-19 Vaccines: A Yearlong Longitudinal and Cross-sectional Study

  • Chunyan Zhang; 
  • Songhua Xu; 
  • Zongfang Li; 
  • Ge Liu; 
  • Duwei Dai; 
  • Caixia Dong

ABSTRACT

Background:

Due to the urgency caused by the COVID-19 pandemic worldwide, vaccine manufacturers have to shorten and parallel the development steps to accelerate the COVID-19 vaccine production. Although all usual safety and efficacy monitoring mechanisms remain in place, varied attitudes towards the new vaccines have arisen among different population groups.

Objective:

This study aims to discern the evolutions and disparities of attitudes among various population groups towards COVID-19 vaccines through the study of long-term and large-scale tweets.

Methods:

We collected over 1.3 billion tweets from June 2020 to July 2021, which covered a yearlong timeline of some most critical phases concerning the development and inoculation of COVID-19 vaccines. We first developed a data mining model that incorporates a series of algorithms for inferring a range of attributes, both in reality and in the cyber space, concerning an online user as well as their sentiments and emotions expressed in tweets. We further conducted an observational study exploring attitudes of major population groups from multiple perspectives, including overall analysis, longitudinal study and cross-sectional study.

Results:

First, the whole population's attention towards vaccines had a strong correlation (Pearson's r=0.9634) with the COVID-19 statistical data, and it was also noticeably and rapidly influenced by major vaccine-related events. Second, there were attitude disparities among population groups with different demographic characteristics. Females' attention ratios towards vaccines were lower than males', with ORs (odds ratio) ranging from 0.44 (95% CI 0.28-0.69) to 0.66 (95% CI 0.50-0.87). Females were initially less positive than males, but eventually became more positive than males after phase III of vaccine development. People 40 years or older always had the highest attention ratios, with ORs ranging from 7.52 (95% CI 6.65-8.51) to 9.69 (95% CI 8.77-10.70). And sentiments of groups of 40 years or older and 18 years or younger tend to be the lowest. Third, vaccine-related tweets had much higher fear proportions and lower joy proportions than general tweets during the study period. After the start of vaccination, fear went down, and joy went up gradually. Finally, the top five countries with the most vaccine-related tweets were the United States, India, United Kingdom, Canada, and Australia.

Conclusions:

This study tracked the yearlong evolutions of attitudes among population groups towards COVID-19 vaccines, and revealed that there were significant disparities of attitudes along multiple dimensions during the study period. These findings can be used as a guide to assist governments and public health organizations to monitor the responses of population groups efficiently. In addition, the method implemented in our study provided a practical approach for tracking and analyzing long-term evolutions of human responses in large scale during any public health event.


 Citation

Please cite as:

Zhang C, Xu S, Li Z, Liu G, Dai D, Dong C

The Evolution and Disparities of Online Attitudes Toward COVID-19 Vaccines: Year-long Longitudinal and Cross-sectional Study

J Med Internet Res 2022;24(1):e32394

DOI: 10.2196/32394

PMID: 34878410

PMCID: 8786033

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