A Sentiment Analysis of Turkish Tweets Shared in Nursing Week During the Pandemic

Autor: Oban, Volkan, Doğan, Muzaffer Berna, Dikeç, Gül
Přispěvatelé: İstinye Üniversitesi, Güzel Sanatlar, Tasarım ve Mimarlık Fakültesi, Dijital Oyun Tasarımı Bölümü, Oban, Volkan, GQZ-0647-2022
Rok vydání: 2022
Předmět:
Zdroj: Sağlık ve Hemşirelik Yönetimi Dergisi. 9:230-238
ISSN: 2149-018X
DOI: 10.54304/shyd.2022.20053
Popis: Aim: This study aimed to conduct an artificial intelligence-based sentiment analysis of Turkish tweets about nursing during the nursing week during the COVID-19 pandemic. Method: This is a retrospective descriptive survey. Between May 4 and May 19, 2021, Turkish tweets were analyzed using the Python library Tweepy. The search terms “nurse, nursing, and nursing week” were used to analyzed tweets for their positivity, neutrality, or negativity. Results: The analysis of 24,944 tweets revealed that tweets frequently express neutral emotions. The negative tweets frequently discussed issues such as societal gender perception, professionalism, burnout during the pandemic, salaries, inadequate nursing workforce, inequalities, violence against healthcare professionals, and the deaths of nurses. Conclusions: Social media applications can be recommended as important tools for raising awareness of the nursing profession identity, professionalism, visibility, and the perception of society towards nursing, nursing problems, and recommendations for solutions.
Databáze: OpenAIRE