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Using Natural Language Processing Techniques to Assess the Attitudes of Nursing Students During the COVID-19 Pandemic

Using Natural Language Processing Techniques to Assess the Attitudes of Nursing Students During the COVID-19 Pandemic
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Author(s): Emine Ela Küçük (Giresun University, Turkey) and Dilek Küçük (Tübitak Marmara Research Center, Turkey)
Copyright: 2022
Pages: 20
Source title: Applications of Computational Science in Artificial Intelligence
Source Author(s)/Editor(s): Anand Nayyar (Duy Tan University, Da Nang, Vietnam), Sandeep Kumar (CHRIST University (Deemed), Bangalore, India) and Akshat Agrawal (Amity University, Guragon, India)
DOI: 10.4018/978-1-7998-9012-6.ch001

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Abstract

COVID-19 pandemic has a significant impact in the world. It has led to different measures taken by governments to prevent its spread, such as school closures, employment of e-learning, and complete lockdowns. Together with the pandemic, these measures also affected many people, economically and psychologically. This chapter assesses the attitudes of undergraduate nursing students in Turkey during the COVID-19 pandemic, using automatic natural language processing (NLP) techniques. NLP is a branch of artificial intelligence, and it facilitates automatic analysis of natural language texts. Machine translation and sentiment analysis are among significant NLP techniques. Data collection is performed using an online questionnaire, filled by 101 students from three different universities in Turkey. Machine translation is used to translate responses of the students to English, and then sentiment analysis is performed on these translations. The sentiment analysis results can be used by related nursing educators and health professionals.

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