Research Article
Covid-19 Vaccination Hesitancy: Sentiment Analysis of Twitter Posts
@INPROCEEDINGS{10.4108/eai.19-5-2023.2334252, author={Dadian Qu and Yuming Chen and Taoyu Mao and Xinyu Dai}, title={Covid-19 Vaccination Hesitancy: Sentiment Analysis of Twitter Posts}, proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2023}, month={7}, keywords={covid-19; sentiment analysis; twitter; opinion mining; vaccination hesitancy}, doi={10.4108/eai.19-5-2023.2334252} }- Dadian Qu
Yuming Chen
Taoyu Mao
Xinyu Dai
Year: 2023
Covid-19 Vaccination Hesitancy: Sentiment Analysis of Twitter Posts
ICBBEM
EAI
DOI: 10.4108/eai.19-5-2023.2334252
Abstract
Many people show concerns about Covid-19 vaccination and choose not to be vaccinated for different reasons. The understanding of those reasons is the key success factor in increasing the uptake rate and control the Covid-19 pandemic. To better understand the public opinions, we use Twitter posts as our dataset since it is highly used to express people’s feelings in many countries. Our study is to use machine learning-based algorithms and human coding methods to perform sentiment analysis, topic modelling, and topic aggregation. We used Vader to filter out positive and neutral tweets. After that, we used LDA to group all the tweets into different clusters. Then we manually aggregated clusters into topics. Our findings show that people have vaccination hesitancy mainly because of the following topics: Safety Concerns; Belief Covid is Harmless; Distrust; Efficacy; Social Distribution.
