간호관련 국민청원 분석: 텍스트네트워크 분석 및 토픽모델링

• Published in: Journal of Korean Academy of Nursing Vol. 53; no. 6; pp. 635 - 651
• Main Authors: 고현정(Ko, HyunJung), 정석희(Jeong, Seok Hee), 이은지(Lee, Eun Jee), 김희선(Kim, Hee Sun)
• Format: Journal Article
• Language: Korean
• Published: 한국간호과학회 2023
• Subjects: Social Network Analysis; 간호; 소셜 네트워크 분석; Nursing; Nurses; 간호사; Data Mining; 데이터 마이닝
• ISSN: 2005-3673; 2093-758X

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.