• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.451-462
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• 2019

Document-term frequency matrix is a type of data used in text mining. This matrix is often based on various documents provided by the objects to be analyzed. When analyzing objects using this matrix, researchers generally select only terms that are common in documents belonging to one object as keywords. Keywords are used to analyze the object. However, this method misses the unique information of the individual document as well as causes a problem of removing potential keywords that occur frequently in a specific document. In this study, we define data that can overcome this problem as proximity data. We introduce twelve methods that generate proximity data and cluster the objects through two clustering methods of multidimensional scaling and k-means cluster analysis. Finally, we choose the best method to be optimized for clustering the object.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.211-218
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• 2023

Due to the implementation of COVID-19 distancing, interest and users in 'home training' are rapidly increasing. Therefore, the purpose of this study is to identify the perception of 'home training' through big data analysis on social media channels and provide basic data to related business sector. Social media channels collected big data from various news and social content provided on Naver and Google sites. Data for three years from March 22, 2020 were collected based on the time when COVID-19 distancing was implemented in Korea. The collected data included 4,000 Naver blogs, 2,673 news, 4,000 cafes, 3,989 knowledge IN, and 953 Google channel news. These data analyzed TF and TF-IDF through text mining, and through this, semantic network analysis was conducted on 70 keywords, big data analysis programs such as Textom and Ucinet were used for social big data analysis, and NetDraw was used for visualization. As a result of text mining analysis, 'home training' was found the most frequently in relation to TF with 4,045 times. The next order is 'exercise', 'Homt', 'house', 'apparatus', 'recommendation', and 'diet'. Regarding TF-IDF, the main keywords are 'exercise', 'apparatus', 'home', 'house', 'diet', 'recommendation', and 'mat'. Based on these results, 70 keywords with high frequency were extracted, and then semantic indicators and centrality analysis were conducted. Finally, through CONCOR analysis, it was clustered into 'purchase cluster', 'equipment cluster', 'diet cluster', and 'execute method cluster'. For the results of these four clusters, basic data on the 'home training' business sector were presented based on consumers' main perception of 'home training' and analysis of the meaning network.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.215-231
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• 2024

The changing media landscape has diversified how and what is discussed about fashion. This study aims to examine expert discussions about fashion shows on social media from the perspective of fashion criticism. To achieve this goal objectively, a text mining program, Leximancer, was used. In total, 58 videos were collected from the panel discussion section of Showstudio from S/S 21 to S/S 24, and the results of text mining on 24,080 collected texts after refinement are detailed here. First, the researchers examined the frequency of keywords by season. This revealed that in 2021-2022, digital transformation, diversity, and fashion films are now commonly used to promote fashion collections, often replacing traditional catwalk shows. From 2023, sustainability and virtuality appeared more frequently, and fashion brands focused on storytelling to communicate seasonal concepts. In S/S 2024, the rise of luxury brand keywords and an increased focus on consumption has been evident. This suggests that it is influenced by social and cultural phenomena. Second, the overall keywords were analyzed and categorized into five concepts: formal descriptions and explanations of the collection's outfits, sociocultural evaluations of fashion shows and designers, assessments of the commerciality and sustainability of the current fashion industry, interpretations of fashion presentations, and discussions of the role of fashion shows in the future. The significance of this study lies in its identification of the specificity of contemporary fashion criticism and its objective approach to critical research.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.73-89
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• 2023

This study aims to analyze the frequency of keywords used in Korean abstracts, which are unstructured text data in the domestic record management research field, using text mining techniques to identify domestic record management research trends through distance analysis between keywords. To this end, 1,157 keywords of 77,578 journals were visualized by extracting 1,157 articles from 7 journal types (28 types) searched by major category (complex study) and middle category (literature informatics) from the institutional statistics (registered site, candidate site) of the Korean Citation Index (KCI). Analysis of t-Distributed Stochastic Neighbor Embedding (t-SNE) and Scattertext using Word2vec was performed. As a result of the analysis, first, it was confirmed that keywords such as "record management" (889 times), "analysis" (888 times), "archive" (742 times), "record" (562 times), and "utilization" (449 times) were treated as significant topics by researchers. Second, Word2vec analysis generated vector representations between keywords, and similarity distances were investigated and visualized using t-SNE and Scattertext. In the visualization results, the research area for record management was divided into two groups, with keywords such as "archiving," "national record management," "standardization," "official documents," and "record management systems" occurring frequently in the first group (past). On the other hand, keywords such as "community," "data," "record information service," "online," and "digital archives" in the second group (current) were garnering substantial focus.

• Journal of Oriental Neuropsychiatry
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• v.22 no.4
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• pp.31-39
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• 2011

Objectives : This study aimed to investigate frequently used herbal materials among herbal prescription for depression focusing on randomized controlled trial. Methods : Every article relevant to depression was initially obtained from China National Infrastructure(CNKI), Korean database and book hand-searching. Searching keywords were 'depression', 'herbal medicine' and 'randomized controllled trial(RCT)'. Results : Among comorbidity with depression, the most accompanied disease was that of circulatory system. Among sixty-five articles, depression with cerebral vascular disease was twenty-eight. Article about mood disorder was twenty-four. High frequently used herbal materials were Bupleuri Radix(41times), Curcumae Radix(34 times), Acori Graminei Rhizoma and Cnidii Rhizoma(24 times). Conclusions : According to this study, we could know select frequent-used herbal medicine. In a clinical treatment, herbal materials can be added herbal prescription related to depression. As these results, it can be helpful to develop new drugs.

• The Journal of Internal Korean Medicine
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• v.36 no.2
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• pp.153-164
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• 2015

Objectives: The aim of this study was to collect and analyze studies on acupuncture therapies for treatment of voiding difficulty in stroke patients and to suggest methods of study for acupuncture therapies. Methods: Electronic searches were performed on search sites including NDSL, 국회도서관, RISS4U, DBPIA, KISS, KMBASE, KoreaMed, 한국전통지식포탈, OASIS, Pubmed, CNKI, using the search words ‘중풍’, ‘뇌졸중’, ‘stroke’, ‘배뇨장애’, ‘voiding’, ‘urinary’, ‘incontinence’, ‘retention’, ‘ ’, ‘침치료’, and ‘acupuncture’ as single or combined keywords, from January 1990 to August 2013 with language limitation, Korean, English, Chinese. Also, quality of the studies were evaluated using Jadad score. Results: The searches identified 16 studies for selection and analysis. In the present study, voiding difficulty includes urinary incontinence and urinary retention. The acupuncture points CV4, SP6, and CV3 were the most frequently used. Treatments were most frequently applied daily. The times and terms of acupuncture treatment, were most frequently 30 minutes per treatment for 4 weeks Conclusions: The acupuncture therapies were effective in the treatment of voiding difficulty in stroke patients, but the study of acupuncture therapy as a treatment for this issue in stroke patients needs to be standardized and high-quality study models should be introduced.

• Journal of Sasang Constitutional Medicine
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• v.31 no.4
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• pp.28-40
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• 2019

Objectives The purpose of this study is to analyze how obesity of Taeeumin have been treated. Methods We searched clinical studies from the databases including Koreanstudies Information Service System(KISS), Oriental medicine Advanced Searching Integrated System(OASIS), Research Information Sharing Service(RISS), National Discovery for Science Leader(NDSL), Korea Citation Index(KCI) and pubmed with the keywords relevant to treatment of Taeeumin obesity. Results A total of 14 studies were analyzed. Herbal medicines were mostly used, and the most frequently used prescription was Taeeumjowi-tang. And concurrent therapies such as diet therapy, exercise therapy, electroacupuncture were performed. Several evaluation methods were used, and patient's body weight was the most used. Conclusion Through this literature review, we could find out tendencies of Korean medicine treatments of obesity of taeeumin up to date and some points that may have clinical significance.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.1-11
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• 2021

The purpose of this study was to analyze the trends and characteristics of 'stress urinary incontinence' research through word frequency analysis, and their relationships were modeled using word embedding. Abstract data of 9,868 papers containing abstracts in PubMed's MEDLINE were extracted using a Python program. Then, through frequency analysis, 10 keywords were selected according to the high frequency. The similarity of words related to keywords was analyzed by Word2Vec machine learning algorithm. The locations and distances of words were visualized using the t-SNE technique, and the groups were classified and analyzed. The number of studies related to stress urinary incontinence has increased rapidly since the 1980s. The keywords used most frequently in the abstract of the paper were 'woman', 'urethra', and 'surgery'. Through Word2Vec modeling, words such as 'female', 'urge', and 'symptom' were among the words that showed the highest relevance to the keywords in the study on stress urinary incontinence. In addition, through the t-SNE technique, keywords and related words could be classified into three groups focusing on symptoms, anatomical characteristics, and surgical interventions of stress urinary incontinence. This study is the first to examine trends in stress urinary incontinence-related studies using the keyword frequency analysis and word embedding of the abstract. The results of this study can be used as a basis for future researchers to select the subject and direction of the research field related to stress urinary incontinence.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.278-291
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• 2016

This study examined research trends via network analyses of keywords appeared in academic research articles about news reports in South Korea during the last 10 years from 2006 to 2015. Keyword network analyses of 4410 keywords from 1108 articles suggested that framing, agenda setting, third-person effect, selective exposure, and uses and gratification were main theories but most studies used framing theory. Research areas included news reports on politics, economics, science, world issues, or tour. However, research on news reports covering culture, sports or daily life were not identified. In terms of media, research on both traditional and emerging media were ample. Research on broadcasting new, online news, and social media were frequently observed.

• International Journal of Contents
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• v.14 no.3
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• pp.27-31
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• 2018

Social network service (SNS) data related to green tourism were used to estimate preferred tour sites and users' interests. Keywords related with green tour activities were employed to search the SNS data. SNS data were collected from Korean blogs such as Naver and Daum from June $1^{st}$ to August $31^{st}$ between 2015 and 2017 using text-mining solution. During the study period, seven hundred and five posts were analyzed. Associated words that frequently co-occurred with keywords were classified into different categories depending on the nature of associated words. Associated words included swimming pools and camping sites (location); experience and swimming pools (attribute); and water play and culture (culture/leisure). Our data suggest that SNS users with experience of green tourism in Korea exhibited interest in green tourism with swimming pools, camping sites, experience, water play and/or culture rather than particular popular sites. Based on the findings, it is recommended that preferred facilities such as swimming pools should be provided at green tourism sites to meet the users' needs and to facilitate green tourism.