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Purpose : This study aimed to analyze research trends on nurse burnout from 2015 to 2024 using text mining and topic modeling, focusing on the structural characteristics and temporal evolution of research themes. Methods : A total of 309 academic papers related to nurse burnout were collected from domestic databases (DBpia, RISS, and KCI). Text preprocessing and frequency analysis were conducted using NetMiner 4.5.1 and Latent Dirichlet Allocation (LDA) was applied to extract latent topics. The optimal number of topics was determined as six based on interpretability and topic coherence. Results : Six major topics were identified: (1) work demand and emotional exhaustion, (2) COVID-19 and occupational resilience, (3) work stress and job satisfaction, (4) clinical work experience, (5) psychological adaptation and mental health, and (6) emotional labor and organizational commitment. Emotional labor and job satisfaction remained central themes throughout the study period, while topics related to resilience and positive psychological capital expanded after the COVID-19 pandemic. The overall trend indicated a gradual shift in research focus from organizational factors to individual psychological resources. Conclusion : Nurse burnout research over the past decade has evolved from focusing on structural work stress to exploring adaptive and preventive factors such as resilience and psychological capital. These findings highlight the need for an integrated approach that combines organizational support and individual resource enhancement to effectively reduce nurse burnout and promote occupational well-being.