Using Twitter for sentiment analysis towards AstraZeneca/Oxford, Pfizer/BioNTech and Moderna COVID-19 vaccines

Abstract

Introduction

A worldwide vaccination campaign is underway to bring an end to the SARS-CoV-2 pandemic; however, its success relies heavily on the actual willingness of individuals to get vaccinated. Social media platforms such as Twitter may prove to be a valuable source of information on the attitudes and sentiment towards SARS-CoV-2 vaccination that can be tracked almost instantaneously.

Materials and methods

The Twitter academic Application Programming Interface was used to retrieve all English-language tweets mentioning AstraZeneca/Oxford, Pfizer/BioNTech and Moderna vaccines in 4 months from 1 December 2020 to 31 March 2021. Sentiment analysis was performed using the AFINN lexicon to calculate the daily average sentiment of tweets which was evaluated longitudinally and comparatively for each vaccine throughout the 4 months.

Results

A total of 701 891 tweets have been retrieved and included in the daily sentiment analysis. The sentiment regarding Pfizer and Moderna vaccines appeared positive and stable throughout the 4 months, with no significant differences in sentiment between the months. In contrast, the sentiment regarding the AstraZeneca/Oxford vaccine seems to be decreasing over time, with a significant decrease when comparing December with March (p<0.0000000001, mean difference=−0.746, 95% CI=−0.915 to −0.577).

Conclusion

Lexicon-based Twitter sentiment analysis is a valuable and easily implemented tool to track the sentiment regarding SARS-CoV-2 vaccines. It is worrisome that the sentiment regarding the AstraZeneca/Oxford vaccine appears to be turning negative over time, as this may boost hesitancy rates towards this specific SARS-CoV-2 vaccine.