인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
The COVID-19 pandemic has significantly increased the amount of time people have spent at home, leading to a heightened interest in interior design. It has also boosted purchases through online platforms. Consequently, furniture and interior design companies that previously focused on offline sales have started to shift their focus to the online market. However, analysis of the online market is still lacking in the interior design industry, which has traditionally been dominated by offline market sales. This study proposes utilizing LDA (Latent Dirichlet Allocation) topic modeling to identify interior design trends by space, based on customer post data from online platforms. To empirically validate this approach, data from Hanssem Mall, leading the interior design market in South Korea, was used to extract interior design trends for each space. Our findings reveal that product-related topics dominate discussions in living rooms, children’s rooms, studies, and balconies. In contrast, brand-related topics are more significant in kitchens. Design-related topics are most relevant for bedrooms, dressing rooms, bathrooms, and dining rooms, while size and specification-related topics are prominent for entrance areas. These insights provide richer information compared to traditional trend analysis that only utilized post titles, enabling more accurate and detailed trend analysis by space. This study provides valuable insights into consumer interest in online platforms through real-world data.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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