디자인 분야의 연구동향 파악: 텍스트 마이닝 기법을 활용하여

· Research Topic: Research presents analysis results using text mining techniques to identify research trends in the field of design. In other words, this study investigates papers in the field of design published in Korean registered papers over the past four years and compares the analysis results by year to make it easier to grasp the research flow in the field of design. · Research background: Analyzing and presenting recent research trends in the field of design can help subsequent researchers select research topics by presenting useful information for research development in the field of design. · Differences from prior research: First, this paper collected abstracts and titles of papers published in Korean registered journals over the past four years and presented annual analysis results to understand the trend of studies in the field of design. This is the first study conducted in Korea to understand the research flow in the design field. Second, various analysis results were presented by presenting the results of word crowd analysis, TF-IDF analysis, and topic modeling analysis among text mining techniques, and the research results of this paper presented through such various analysis can be said to be objective and reliable. · Research Method: From 2020 to 2023, thesis abstracts and titles on 'design' searched on Naver thesis sites were collected. Python 3.11.2 was used to collect thesis data, and BeautifulSoup and Selenium, packages dedicated to Crawling, were used. Data were crawled from 307 cases in 2020, 252 cases in 2021, 1,052 cases in 2022, and 359 cases in 2023. From the collected data, nouns were extracted using Konlpy's Okt, a Korean morpheme analyzer. In this paper, word crowd analysis, keyword analysis, and topic modeling analysis among text mining techniques are performed to derive research results. · Research Results: The summary of the research results of this paper is as follows. First, the results of the word crowd analysis are as follows. Words such as 'design', 'research', 'analysis', and 'utilization' are common in the analysis results of each state, so the corresponding words were excluded to compare significant differences. WordCloud in 2020 shows that words such as 'social', 'class', 'brand', 'experience' and 'service' appear frequently. WordCloud in 2021 shows that words such as 'consumer', 'class', 'visual', 'environment' and 'product' appear frequently. WordCloud in 2022 shows that words such as 'experience', 'product', 'culture', 'service' and 'environment' appear frequently. Finally, WordCloud in 2023 shows that words such as 'environment', 'brand', 'city', 'culture' and 'experience' appear frequently. Second, the results of the TF-IDF analysis are as follows. In 2020, keywords related to research in the field of design were derived in the order of space, class, experience, service, society, program, brand, problem, environment, and change. In 2021, keywords related to research in the field of design were derived in the order of space, society, environment, service, consumer, class, product, value, change, and brand. And in 2022, keywords related to research in the field of design were derived in the order of space, use, culture, environment, product, proposal, society, service, experience, and change. Finally, in 2023, keywords related to research in the field of design were derived in the order of space, service, society, culture, city, environment, brand, change, proposal, and use. Third, as a result of the topic modeling analysis of research in the design field in 2020, the main keywords of Topic 1 were "infant," "program," "class," and the main keywords of Topic 2 were "walking," "means," "senior," "crime prevention," "user," and Topic 3 were "virtual," "augmented reality," and "reality." As a result of the topic modeling analysis of research in the design field in 2021, the main keywords of Topic 1 were 'visual', 'consumer', 'impact', 'smart', 'vehicle', 'interface', 'smartphone', and the main keywords of Topic 3 were 'workshop', 'untact', 'competence', 'creation', and 'computer'. As a result of the topic modeling analysis of research in the design field in 2022, the main keywords of Topic 1 were 'table', 'frame', 'web design', and the main keywords of Topic 2 were 'emotional', 'mobile', 'branding', 'ideal', 'fun', and Topic 3 were derived as 'geppetto', 'art', 'computing', and 'creativity'. Finally, as a result of the topic modeling analysis of research in the design field in 2023, the main keywords of Topic 1 were 'the elderly', 'safety', 'children', 'society', and the main keywords of Topic 2 were 'creativity', 'class', 'university', 'knowledge', 'accident', 'mobile', 'dimensional', and 'trend'. · Contribution points and expected effects: First, this paper provides useful information to researchers in the design field by objectively analyzing recent research trends in the design field and presenting results. Second, this study presented meaningful research trend information using various text mining techniques, and this research methodology is expected to be a good guideline for subsequent researchers.