Exploring Depression Research Trends Using BERTopic and LDA

• 영문명: Exploring Depression Research Trends Using BERTopic and LDA
• 발행기관: 한국식품보건융합학회
• 저자명: Woo-Ryeong YANG Hoe-Chang YANG
• 간행물 정보: 『식품보건융합연구』제9권 1호, 19~28쪽, 전체 10쪽
• 주제분류: 복합학 > 과학기술학
• 파일형태: PDF
• 발행일자: 2023.02.28

영문 초록

The purpose of this study is to explore which areas have been more interested in depression research in Korea through analysis of academic papers related to depression, and then to provide insights that can solve future depression problems. 1,032 papers searched with the keyword “depression” in scienceON were analyzed using Python 3.7 for word frequency analysis, word co-occurrence analysis, BERTopic, LDA, and OLS regression analysis. The results of word frequency and co-occurrence frequency analysis showed that related words were composed around words such as patient, disorder and symptom. As a result of topic modeling, a total of 13 topics including 'childhood depression' and 'eating anxiety' were derived. And it has been identified as a topic of interest that 'suicidal thoughts', 'treatment', 'occupational health', and 'health treatment program' were statistically significant topics, while 'child depression' and 'female treatment' were relatively less. As a result of the analysis of research trends, future research will not only study physiological and psychological factors but also social and environmental causes, as well as it was suggested that various collaborative studies of experts in academia were needed such as convergence and complex perspectives for depression relief and treatment.

키워드

Depression Depression Disorder Research Trend BERTopic LDA