A Sentiment Analysis of Turkish Tweets Shared in Nursing Week During the Pandemic
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Date
2022
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Association of Executive Nurses
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Abstract
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. © 2022 The Authors. Published by Association of Nurse Managers.
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Artificial Intelligence, Natural Language Processing, Nursing, Social Media
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Source
Journal of Health and Nursing Management
Volume
9
Issue
2
Start Page
230
End Page
238