• Journal of Fashion Business
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• v.23 no.3
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• pp.51-66
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• 2019

The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.

• Korean Journal of Childcare and Education
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• v.20 no.1
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• pp.91-111
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• 2024

Objective: The purpose of this study is to explore trends in institutional evaluation research in early childhood education through keyword network analysis. This aims to understand trends in academic discourse on institutional evaluation and gain implications for follow-up research and related policy directions. Methods: A total of 6,629 keywords were extracted from 572 dissertations and journal articles published from January 2006 to October 2023 for the purpose of analyzing and visualizing the frequency and centrality of keywords, as well as the structural properties of keyword networks. The analysis and visualization were conducted using the TEXTOM, UCINET6, and NetDraw programs. Results: First, the number of institutional evaluation studies increased steadily from 2006 to 2010 and then decreased, with a higher frequency of studies on daycare centers compared to kindergartens. Second, the most frequently occurring keyword in the analysis was 'daycare center,' and the highest connection strength was found in the term 'daycare-center-evaluation.' Third, network analysis revealed that key terms for institutional evaluation research included 'evaluation certification,' 'recognition,' 'evaluation indicators,' 'teacher,' 'daycare center,' and 'kindergarten.' In the ego network analysis for each institution, 'parent' emerged as a highly ranked keyword. Conclusion/Implications: This study confirmed the perspectives of previous studies by revealing the structure of core concepts in early childhood education institution evaluation research, and provided implications for follow-up and direction of institution evaluation

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.53-60
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• 2018

Domestic public e-procurement has been recognized excellence at home and abroad. However, it is difficult for procurement companies to check the related announcements and to grasp the status of procurement announcements at a glance. In this paper, we propose an e-Procurement Announcement Analysis Support System using the HDFS, HDFS, Apache Spark, and Collaborative Filtering Technology for procurement announcement recommendation service and procurement announcement and contract trend analysis service for effective e-procurement system. Procurement announcement recommendation service can relieve the procurement company from searching for announcements according to the characteristics and characteristics of the procurement company. The procurement announcement/contract trend analysis service visualizes the procurement announcement/contract information and procures It is implemented so that the analysis information of electronic procurement can be seen at a glance to the company and the demand organization.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.538-553
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• 2021

As interest in the sustainable fashion industry continues to increase along with climate issues, it is necessary to identify research trends in sustainable fashion and seek new development directions. Therefore, this study aims to analyze research trends on sustainable fashion. For this purpose, related papers were collected from the KCI (Korean Citation Index) and Scopus, and 340 articles were used for the study. The collected data went through data transformation, data preprocessing, topic modeling analysis, core topic derivation, and visualization through a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: consumer clothing consumption behavior and environment, upcycle product development, product types by environmental approach, ESG business activities, materials and material development, process-based approach, lifestyle and consumer experience, and brand strategy. Topics were related to consumption, production, and education of sustainable fashion, respectively. KCI analysis results and Scopus analysis results derived eight topics but showed differences from the comprehensive analysis results. This study provides primary data for exploring various themes of sustainable fashion. It is significant in that the data were analyzed based on probability using a research method that excluded the subjective value of the researcher. It is recommended that follow-up studies be conducted to examine social trends.

• Journal of Information Science Theory and Practice
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• v.9 no.3
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• pp.76-106
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• 2021

The study analyzed bibliometric data of papers published in Korea Citation Index (KCI) and Web of Science (WoS) journals from 2002 to 2021. After examining size differences of KCI and WoS domains in the number of authors, institutions, and journals to put publication and citations counts in perspective, the study investigated co-authorship patterns over time to compare collaboration trends of Korean and international scholars and analyzed the data at author, institution, and journal levels to explore how the influences of authors, institutions, and journals on research output differ across domains. The study also conducted frequency-based analysis of keywords to identify key topics and visualized keyword clusters to examine topic trends. The result showed Korean LIS authors to be twice as productive as international authors but much less impactful and Korean institutions to be at comparable levels of productivity and impact in contrast to much of productivity and impact concentrated in top international institutions. Citations to journals exhibited initially increasing pattern followed by a decreasing trend though WoS journals showed far more variance than KCI journals. Co-authorship trends were much more pronounced among international publication, where larger collaboration groups suggested multi-disciplinary and complex nature of international LIS research. Keyword analysis found continuing diversification of topics in international research compared to relatively static topic trend in Korea. Keyword visualization showed WoS keyword clusters to be much denser and diverse than KCI clusters. In addition, key keyword clusters of WoS were quite different from each other unlike KCI clusters which were similar.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.5
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• pp.672-682
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• 2015

SPA brands have quickly expanded in domestic fashion markets as native SPA brands enter markets that foreign SPA brands previously occupied. It is important that each SPA brand establish its own brand identity to differentiate itself from other brands when SPA brand competition in fashion markets increases. This study investigates how SPA brands express brand identities through colors due to their importance for visualization strategies and brand identity. This study conducted a simultaneous literature study and case study. First, this study reviewed the theoretical background of brand identity and its relationship with colors as well as SPA brands by studying relevant literature and cases of domestic academic theses and data on Internet web sites. After reviewing the theoretical background of SPA brands, this study selected 4 stores of SPA brands (8SECONDS, H&M, UNIQLO, and ZARA) as case study targets and analyzed the stores' external appearance, interior and product colors. Store analysis divided colors into identity colors and trend colors with each SPA company expressing its own brand identity through: the store's external appearance (logo color), painted interior colors (ceiling, floor, walls, mannequins, hangers, equipment, and store-carrier bag), or trend colors (reflected in the store's main display hall or products). The results consider that each SPA brand sets the mass market as their target, and chooses the commercialization of latest fashion by selecting the latest trends in the fashion trend cycle, so its products do not reflect characteristics symbolizing the company's uniqueness and brand.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Tunnel and Underground Space
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• v.25 no.4
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• pp.303-319
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• 2015

Text mining is one of the branches of data mining and is used to find any meaningful information from the large amount of text. In this study, we analyzed titles and keywords of two SCI journals on rock engineering by using text mining to find major research area, trend and associations of research fields. Visualization of the results was also included for the intuitive understanding of the results. Two journals showed similar research fields but different patterns in the associations among research fields. IJRMMS showed simple network, that is one big group based on the keyword 'rock' with a few small groups. On the other hand, RMRE showed a complex network among various medium groups. Trend analysis by clustering and linear regression of keyword - year frequency matrix provided that most of the keywords increased in number as time goes by except a few descending keywords.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.166-171
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• 2024

Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

• Archives of design research
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• v.16 no.3
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• pp.101-110
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• 2003

People are surrounded with numerous sounds. The sound is generated from nature and people. For example, the sound enables people or animal responsive to instinctive action. Music or fine arts are presented differently by its distinctive medium. On the other hand, those art forms are similar in a way that people uses right side of brain and intuitions for creative effects. Conjunctions between sounds and visual arts have been progressed to data. From art forms in subjective views to art forms using high technology such as the computer, experiments for sounds visualization are practiced constantly. For that reason, intrinsic attributes of sounds in design area and distinctive qualities are discussed in this study. With respect to existing category of studies and consideration of the tendency in recent researches, the object is to propose direction for the study in regards to methodology of design, which is reconstructing visualized expression.