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

¹Arel University, Faculty of Health Sciences, Department of Nursing, Istanbul, Turkey
²Istinye University, Faculty of Fine Arts, Design and Architecture, Department of Digital Game Design, Istanbul, Turkey
³Fenerbahce University, Faculty of Health Sciences, Department of Nursing, Istanbul, Turkey

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.

Keywords:

K�resel Salg�n S�recindeki Hem�irelik Haftas�nda Payla��lan T�rk�e Twitter �letilerinin Duygu Analizi

¹Arel �niversitesi, Sa�l�k Bilimleri Fak�ltesi, Hem�irelik B�l�m�, �stanbul, T�rkiye
²�stinye �niversitesi, G�zel Sanatlar, Tasar�m ve Mimarl�k Fak�ltesi, Dijital Oyun Tasar�m� B�l�m�, �stanbul, T�rkiye
³Fenerbah�e �niversitesi, Sa�l�k Bilimleri Fak�ltesi, Hem�irelik B�l�m�, �stanbul, T�rkiye

Ama�: Bu �al��man�n amac�, COVID-19 k�resel salg�n� s�recinde hem�irelik haftas�n� da i�eren iki haftal�k bir d�nemde hem�irelikle ilgili T�rk�e iletilerin (tweet) yapay zek� tabanl� duygu analizini yapmakt�r.
Y�ntem: �al��ma retrospektif, tan�mlay�c� olarak ger�ekle�tirilmi�tir. T�rk�e iletiler 04-19 May�s 2021 tarihleri aras�nda �hem�ire, hem�irelik, hem�irelik haftas�� anahtar s�zc�kleri kullan�larak, Python Library Tweepy ile analiz edilmi�tir.
Bulgular: Toplam 24.944 ileti belirlenmi�tir. Yapay zekaya dayal� duygu analizi ger�ekle�tirilen �al��man�n sonucunda, hem�irelikle ilgili iletilerin genellikle yans�z/tarafs�z duygular i�erdi�i g�r�lm��t�r. Olumsuz iletilerde s�kl�kla hem�irelerin ya�ad�� sorunlar dile getirilmi�tir. �letilerde belirtilen sorunlar�n; hem�ireli�in toplumsal cinsiyet alg�s�, hem�ireli�in profesyonelli�i, salg�n d�neminde t�kenmi�lik, d��k maa�lar, hem�irelik i�g�c�n�n yetersizli�i ve e�itsizlikler, sa�l�k �al��anlar�na y�nelik �iddet ve hem�ire �l�mleri vb. ilgili oldu�u belirlenmi�tir.
Sonu�: Toplumun hem�ireli�e y�nelik alg�s�, hem�irelik sorunlar�, hem�irelik mesle�inin kimli�i, profesyonelli�i ve g�r�n�rl�� ile ilgili fark�ndal��n art�r�lmas� i�in sosyal medya uygulamalar�n�n kullan�lmas� �nerilebilir.

Anahtar Kelimeler:

Muzaffer Berna Do�an, Volkan Oban, G�l Dike�. A Sentiment Analysis of Turkish Tweets Shared in Nursing Week During the Pandemic. Journal of Health and Nursing Management. 2022; 9(2): 230-238

Corresponding Author: Muzaffer Berna Do�an, T�rkiye