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KMID : 0806120230530010055
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대한간호학회지
2023 Volume.53 No. 1 p.55 ~ p.68
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Keyword Network Analysis and Topic Modeling of News Articles Related to Artificial Intelligence and Nursing
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Ha Ju-Young
Park Hyo-Jin
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Abstract
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Purpose: The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing.
Methods: After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4.
Results: As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were ’education,’ ‘medical robot,’ and ‘fourth industry.’ Five topics were derived from news articles related to artificial intelligence and nursing: ‘Artificial intelligence nursing research and development in the health and medical field,’ ‘Education using artificial intelligence for children and youth care,’ ‘Nursing robot for older adults care,’ ‘Community care policy and artificial intelligence,’ and ‘Smart care technology in an aging society.’
Conclusion: The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.
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KEYWORD
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Artificial Intelligence, Nursing, Social Network Analysis, Newspaper Article
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