• Title/Summary/Keyword: co-word analysis

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Research on Ways to Revitalize Traditional Markets by Exploring Research Trends (연구동향 탐색을 통한 전통시장 활성화 방안 연구)

  • Choon-Ho LEE;Hoe-Chang YANG
    • The Journal of Economics, Marketing and Management
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    • v.11 no.4
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    • pp.53-63
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    • 2023
  • Purpose: The purpose of this study is to examine the research trends in the papers published by Korean researchers related to traditional markets, to check what topics have been studied, and to make various suggestions for research directions and effective ways to revitalize traditional markets. Research design, data and methodology: To this end, this study conducted word frequency analysis, co-occurrence frequency analysis, BERTopic, LDA, dynamic topic modeling and OLS regression analysis using Python 3.7 on the English abstracts of a total of 502 papers extracted through ScienceON. Results: As a result of word frequency analysis and co-occurrence frequency analysis, it was found that studies related to traditional markets have been conducted not only on factors related to customers, but also on traditional market merchants and government policies, and the degree of service, quality, and satisfaction perceived by customers using traditional markets. Through BERTopic and LDA, three topics such as 'Traditional market safety management' were identified, and among them, it was found that 'Traditional market safety management' is relatively less attention by researchers. Conclusions: The results of this study suggest that future research on the revitalization of traditional markets should be conducted from a specific consulting perspective along with the establishment of various data, a causal model study from various perspectives such as the characteristics of merchants as well as consumers, and an integrated and convergent approach to policy formulation by the government and local governments.

A Study on the Intellectual Structure of Metadata Research by Using Co-word Analysis (동시출현단어 분석에 기반한 메타데이터 분야의 지적구조에 관한 연구)

  • Choi, Ye-Jin;Chung, Yeon-Kyoung
    • Journal of the Korean Society for information Management
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    • v.33 no.3
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    • pp.63-83
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    • 2016
  • As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word 'metadata'. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.

Analysis of Laughter Therapy Trend Using Text Network Analysis and Topic Modeling

  • LEE, Do-Young
    • Journal of Wellbeing Management and Applied Psychology
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    • v.5 no.4
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    • pp.33-37
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    • 2022
  • Purpose: This study aims to understand the trend and central concept of domestic researches on laughter therapy. For the analysis, this study used total 72 theses verified by inputting the keyword 'laughter therapy' from 2007 to 2021. Research design, data and methodology: This study performed the development and analysis of keyword co-occurrence network, analyzed the types of researches through topic modeling, and verified the visualized word cloud and sociogram. The keyword data that was cleaned through preprocessing, was analyzed in the method of centrality analysis and topic modeling through the 1-mode matrix conversion process by using the NetMiner (version 4.4) Program. Results: The keywords that most appeared for last 14 years were laughter therapy, depression, the elderly, and stress. The five topics analyzed in thesis data from 2007 to 2021 were therapy, cognitive behavior, quality of life, stress, and the elderly. Conclusions: This study understood the flow and trend of research topics of domestic laughter therapy for last 14 years, and there should be continuous researches on laughter therapy, which reflects the flow of time in the future.

A Study on Web Archiving Subject Analysis Based on Network Analysis (네트워크 분석을 기반으로 한 웹 아카이빙 주제영역 연구)

  • Kim, Hee-Jung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.22 no.2
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    • pp.235-248
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    • 2011
  • In this study, co-word occurrence analysis was performed on 288 articles rerieved from the Web of Science DB with the topic of web archiving. Results showed that research on image archiving information technology and system were most frequently carried out especially in medical area. Within library and information science and records management & archives areas, web archiving/digital preservation project subject and web archiving tools and methodology subject were studied mostly. It is expected that research related to web archiving software and tools will be increased in near future.

Linking Service Perception to Intention to Return and Word-of-Mouth about a Restaurant Chain: Empirical Evidence

  • GARA, Edwen Huang;GARA, Edwin Huang;RAHMAN, Fathony;WIBOWO, Alexander Joseph Ibnu
    • Journal of Distribution Science
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    • v.21 no.1
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    • pp.73-83
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    • 2023
  • Purpose: This study analyzed the influence of restaurant service perception on customer satisfaction and its implications on customers' attitude towards, intention to return to, and word-of-mouth (WOM) regarding a restaurant chain. Research design, data and methodology: Data from 421 respondents were collected using the convenience sampling method. After analyzing the data normality and removing responses with missing data and outliers, 342 responses were selected for further analysis, and the hypotheses were tested using Structural Equation Modeling (SEM). Results: We found that service perception affected customer satisfaction and customer satisfaction affected the customers' attitude toward the restaurant chain, which affected customers' intention to return and WOM about the restaurant chain. Conclusions: This paper provides one of the most important empirical results for managers in the restaurant sector, especially in Indonesia. Restaurant managers should thus provide training to their employees to improve the quality of the interaction with the customers and thereby increase customer satisfaction. The limitations listed in this study include the exclusion of respondents' income. For future research, we suggest investigating models of customer participation or consumer value co-creation for restaurant marketing success. Consumers are generic actors in the service ecosystem engaged in the value co-creation process.

An Informetric Study on Academic Activities and Environmental Movements in Solving Global Environmental Problems (지구적 환경문제 해결을 위한 학술활동과 환경운동 경향 연구)

  • Park, Jae-Shin;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.27 no.3
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    • pp.83-102
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    • 2010
  • This study aims to understand and compare the characteristics of two major approaches to solving global environmental problems - an academic approach including scholarly activities of environmental sciences and a practical approach of environmental movements led by NGOs - by employing informetric analysis methods. Knowledge structure of environmental sciences is depicted through co-citation networks of subject categories assigned to the cited journals in the discipline of environmental sciences for the 10-year period from 2000 to 2009. Furthermore, major interests of environmental NGOs are identified on the basis of external link data collected from web sites of the NGOs. Co-word analyses are also performed using the texts of journal papers in environmental sciences as well as news articles provided by NGO sites. Through the analyses, dominant subject areas of environmental sciences and environmental movements are identified demonstrating similarities and differences between the two approaches.

Comparative analysis on design key-word of the four major international fashion collections - focus on 2018 fashion collection - (4대 해외 패션 컬렉션의 디자인 key-word 비교분석 - 2018년 패션 컬렉션을 중심으로 -)

  • Kim, Sae-Bom;Lee, Eun-Suk
    • Journal of the Korea Fashion and Costume Design Association
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    • v.21 no.3
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    • pp.109-119
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    • 2019
  • The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

Domain Analysis of Research on Prediction and Analysis of Slope Failure by Co-Word Analysis (동시출현단어 분석을 활용한 비탈면 붕괴 예측 및 분석 연구에 관한 지적구조 분석)

  • Kim, Sun-Kyum;Kim, Seung-Hyun
    • The Journal of Engineering Geology
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    • v.31 no.3
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    • pp.307-319
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    • 2021
  • Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.

Microplastics Intellectual Network Analysis based on Bigdata (빅데이터 기반한 미세플라스틱 지적네트워크 분석)

  • Kim, Younghee;Chang, Kwanjong
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.239-259
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    • 2022
  • Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

Identifying Hazard of Fire Accidents in Domestic Manufacturing Industry Using Data Analytics (국내 제조업 화재사고 데이터 분석을 통한 복합 유해·위험요인 확인)

  • Kyung Min Kim;Yongyoon Suh;Jong Bin Lee;Seong Rok Chang
    • Journal of the Korean Society of Safety
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    • v.38 no.4
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    • pp.23-31
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    • 2023
  • Revising the Occupational Safety and Health Act led to enacting and revising related laws and systems, such as placing fire observers in hot workplaces. However, the operating standards in such cases are still ambiguous. Although fire accidents occur through multiple and multi-step factors, the hazards of fire accidents have been identified in this study as individual rather than interrelated factors. The aim has been to identify multiple factors of accidents, outlining fire and explosion accidents that recently occurred in the domestic manufacturing industry. First, major keywords were extracted through text mining. Then representative accident types were derived by combining the main keywords through the co-word network analysis to identify the hazards and their relationships. The representative fire accidents were identified as six types, and their major hazards were then addressed for improving safety measures using the identification of hazards in the "Risk Assessment" tool. It is found that various safety measures, such as professional fire observers' training and clear placement standards, are needed. This study will provide useful basic data for revising practical laws and guidelines for fire accident prevention, system supplementation, safety policy establishment, and future related research.