Discussions about COVID-19 Vaccination on Twitter in Turkey: Sentiment Analysis
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Cambridge University Press
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Objectives: The present study aims to examine coronavirus disease 2019 (COVID-19) vaccination discussions on Twitter in Turkey and conduct sentiment analysis. Methods: The current study performed sentiment analysis of Twitter data with the artificial intelligence (AI) Natural Language Processing (NLP) method. The tweets were retrieved retrospectively from March 10, 2020, when the first COVID-19 case was seen in Turkey, to April 18, 2022. A total of 10,308 tweets accessed. The data were filtered before analysis due to excessive noise. First, the text is tokenized. Many steps were applied in normalizing texts. Tweets about the COVID-19 vaccines were classified according to basic emotion categories using sentiment analysis. The resulting dataset was used for training and testing ML (ML) classifiers. Results: It was determined that 7.50% of the tweeters had positive, 0.59% negative, and 91.91% neutral opinions about the COVID-19 vaccination. When the accuracy values of the ML algorithms used in this study were examined, it was seen that the XGBoost (XGB) algorithm had higher scores. Conclusions: Three of 4 tweets consist of negative and neutral emotions. The responsibility of professional chambers and the public is essential in transforming these neutral and negative feelings into positive ones. © 2022 The Author(s). Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health, Inc.
Açıklama
Anahtar Kelimeler
COVID-19, sentiment analysis, Twitter, vaccine, artificial intelligence, drug therapy, epidemiology, human, prevention and control, retrospective study, social media, turkey (bird), vaccination, Artificial Intelligence, COVID-19, COVID-19 Vaccines, Humans, Retrospective Studies, Sentiment Analysis, Social Media, Turkey, Vaccination
Kaynak
Disaster Medicine and Public Health Preparedness
WoS Q Değeri
Scopus Q Değeri
Q2
Cilt
17
Sayı
7
