Public's perception on nursing education during the COVID-19 pandemic: SENTIMENT analysis of Twitter data

With the emergence of nurses as heroes on the front lines during the COVID-19 pandemic, posts on Twitter about nursing and nursing education began to increase. This study aims to make a sen-timent analysis on Twitter posts regarding society's perception of nursing education during the COVID-19 pandemic and to shed light on concerns, sentiments, and experiences related to nurs-ing education during the pandemic. The text mining method was used to analyze the sentiment analysis of Twitter data. Between July 1st, 2021, and July 1st, 2022, during the COVID-19 pan-demic, a total of 30,194. Twitter messages in English were analyzed using the "nursing educa-tion" hashtag and keyword. All data cleaning and analysis were carried out with R software, and the tweet data set was analyzed using the frequency of keywords and sentiment analysis. Senti-ment analysis of each tweet was conducted using various sentiment analysis dictionaries. The re-sults showed that nursing, education, health, school, and nurses were the most used keywords. In the sentiment analysis conducted during the pandemic, 84 % of the tweets comprised positive, 12 % negative, and 4 % neutral sentiments. The conclusions highlight the importance of knowing and appreciating the contributions of nurses and nursing students during the pandemic and sup-porting more nurse professionals during crises such as the COVID-19 pandemic by addressing the problems during nursing education.