Comparison between Online Social Media Discussions and Vaccination Rates

Continuing our work on social media and vaccinations,  Qingqing Chen, Arie Croitoru, and myself have a new paper entitled "A comparison between online social media discussions and vaccination rates: A tale of four vaccines" published in DIGITAL HEALTH. In the paper we explore online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) as captured on Twitter in the United States (US) from 2015 to 2021.

By using machine learning models (e.g., Naive Bayes, support vector machine (SVM), logistic regression, and extreme gradient boosting (XGBoost)) on over  11.7 million Twitter messages sent by approximately 2.6 million distinct users we found that while the COVID-19, it has come to dominate the vaccination discussion, there was an apparent discrepancy between the online debates and the actual vaccination rates in the US. 

If this sounds of interest and you wish to find out more, below we provide the abstract to to the paper, some figures which captures our workflow and a sample of the results such as a comparison between different vaccine discussions on Twitter and the actual vaccination rate. Finally at the bottom of the page you can find the full reference and a link to the paper.

Abstract: 

The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown. Furthermore, the question of whether there is a discrepancy between people's opinions as expressed online and their actual decision to vaccinate remains open. To shed light on this issue, in this paper we examine the dynamics of online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) through the lens of public attention as captured on Twitter in the United States from 2015 to 2021. We then compare this to actual vaccination rates from governmental reports, which we argue serve as a proxy for real-world vaccination behaviors. Our results demonstrate that since the outbreak of COVID-19, it has come to dominate the vaccination discussion, which has led to a redistribution of attention from the other three vaccination themes. The results also show an apparent discrepancy between the online debates and the actual vaccination rates. These findings are in line with existing theories, that of agenda-setting and zero-sum theory. Furthermore, our approach could be extended to assess the public's attention toward other health-related issues, and provide a basis for quantifying the effectiveness of health promotion policies.

Keywords:  COVID-19, Influenza, MMR, HPV, Social media, Vaccination.

 

The workflow for comparing between online social media discussion and vaccination rates.

The quarterly distribution of percentage of users by different vaccine discussion from 2015 to 2021.

 The comparison between different vaccine discussions on Twitter and growth rate of the actual vaccination rate collected from the CDC (a) COVID-19; (b) Influenza; (c) HPV; (d) MMR.

The changes of emotion over time for different vaccines.

Full reference: 

Chen Q, Croitoru A. and Crooks A.T (2023), A Comparison between Online Social Media Discussions and Vaccination Rates: A tale of four vaccines. DIGITAL HEALTH: 9. doi:10.1177/20552076231155682. (pdf)