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

Abstract

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 sentiment 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 nursing 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 pandemic, a total of 30,194. Twitter messages in English were analyzed using the “nursing education” 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. Sentiment analysis of each tweet was conducted using various sentiment analysis dictionaries. The results 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 supporting more nurse professionals during crises such as the COVID-19 pandemic by addressing the problems during nursing education.