Understanding what do Thai people think about different kinds of COVID-19 vaccines using text mining

Abstract

The research aimed to apply text mining techniques to analyze the opinion of Thai people about the Covid-19 vaccine. Thai Twitter data used in this study was searched through keywords related to Covid-19 vaccine brand names: AstraZeneca, Sinovac, Sinopharm, Pfizer, and Moderna from March to October 2021. There were 451,209 tweets. All the tweets collected were separated on Covid-19 vaccine brand names and then classified topics using with Latent Dirichlet Allocation (LDA) technique. Next, sentiment analysis of the tweets on different topics was done using the Multinomial Logistic Regression Model. As a result, tweets related to the AstraZeneca vaccine can be classified into 8 topics. Most of them illustrated the Mix and match of different Covid-19 vaccines on Thailand’s vaccination policy, including the side effects. Sinovac vaccine can be classified into 9 topics. Most of the tweets stated that the celebrity getting vaccinated. Sinopharm vaccine can be classified into 10 topics. Most of the tweets talked about the problems of vaccine booking systems. Pfizer vaccine can be classified into 10 topics. Most of the tweets discussed the delay or shortage of place orders for vaccines, whereas Moderna vaccine can be classified into 4 topics. Most of them focused on the problems with the vaccine booking system. In addition, it revealed that most Thai people’s opinions on social media are neutral polarity. Negative sentiment tweets constituted a larger share as compared to positive sentiment tweets about vaccines. Most of the topics in the tweets with negative sentiment involve insufficient vaccines, Covid-19 vaccine procurement management by the government Issues, the online systems of the alternative vaccines defined in Thailand, including side effects after vaccination, and even reviews of vaccinations of Thai celebrities or influencer people.