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National Petition Analysis Related to Nursing: Text Network Analysis and Topic Modeling
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HyunJung Ko, Seok Hee Jeong, Eun Jee Lee, Hee Sun Kim
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J Korean Acad Nurs 2023;53(6):635-651. Published online December 31, 2023
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DOI: https://doi.org/10.4040/jkan.23052
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 Abstract
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- Purpose
This study aimed to identify the main keyword, network structure, and main topics of the national petition related to “nursing” in South Korea.
Methods
Data were gathered from petitions related to the national petition in Korea Blue House related to the topic “nursing” or “nurse” from August 17, 2017, to May 9, 2022. A total of 5,154 petitions were searched, and 995 were selected for the final analysis. Text network analysis and topic modeling were analyzed using the Netminer 4.5.0 program.
Results
Regarding network characteristics, a density of 0.03, an average degree of 144.483, and an average distance of 1.943 were found. Compared to results of degree centrality and betweenness centrality, keywords such as “work environment,” “nursing university,” “license,” and “education” appeared typically in the eigenvector centrality analysis. Topic modeling derived four topics: (1) “Improving the working environment and dealing with nursing professionals,” (2) “requesting investigation and punishment related to medical accidents,” (3) “requiring clear role regulation and legislation of medical and nonmedical professions,” and (4) “demanding improvement of healthcare-related systems and services.” Conclusion: This is the first study to analyze Korea's national petitions in the field of nursing. This study's results confirmed both the internal needs and external demands for nurses in South Korea. Policies and laws that reflect these results should be developed.
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Citations
Citations to this article as recorded by  - Voice of Customer Analysis of Nursing Care in a Tertiary Hospital: Text Network Analysis and Topic Modeling
Hyunjung Ko, Nara Han, Seulki Jeong, Jeong A Jeong, Hye Ryoung Yun, Eun Sil Kim, Young Jun Jang, Eun Ju Choi, Chun Hoe Lim, Min Hee Jung, Jung Hee Kim, Dong Hyu Cho, Seok Hee Jeong
Journal of Korean Academy of Nursing Administration.2024; 30(5): 529. CrossRef - A Study on Internet News for Patient Safety Campaigns: Focusing on Text Network Analysis and Topic Modeling
Sun-Hwa Shin, On-Jeon Baek
Healthcare.2024; 12(19): 1914. CrossRef
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