• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.305-318
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• 2024

Purpose - The purpose of this study was to conduct a preliminary study to identify key trends on research articles indexed in KCI in relation to tourism in Jeju and sports tourism. Design/methodology/approach - Information regarding research articles focused on Jeju tourism and sports tourism indexed in KCI (145 and 120 articles respectively) were collected and finally abstract written in Korean of 100 and 91 articles on sports tourism and Jeju tourism respectively were chosen for the further analysis after removing redundant articles. R program was used to analyze keyword frequencies, co-occurring terms, and degree/betweeness centrality measures and visualize the keyword network results. Findings - Event, marketing, content, program, implication, service, stadium, and tourism destination have been identified as keywords with highest frequencies among research on sport tourism, whereas tourism destination, image, brand, content, data, Chinese, satisfaction, eco-tourism service, place of arrival were highly appearing terms among research on Jeju tourism. Research implications or Originality - This study highlighted that Jeju has been interlinked with a range of terms such as programs influencing Jeju tourism, natural environment, tourism-related resources (e.g., museums, dramas, etc.), whereas sports has been closely related to sports event and vaiours types of sports (e.g., bicycle, staking, and scuber), but not to Jeju-do.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.403-410
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• 2017

Apartment housing has rapidly increased since the housing supply policy implemented in the late 1980s. However, various defects have occurred because the policy focused only on quantity supply, while neglected quality control. In addition, disputes related to various defects are increasing. ; accordingly, studies defects of apartment houses have been continuously conducted to solve various problems. In this study, I analyzed the research trends regarding long-term accumulated defects of apartment buildings by keyword network analysis, and suggest implications. As ananalysis method, I collected journal articles using the portal of the Korea Educational and Scientific Information Agency and constructed data analysis by filtering collected academic papers and keyword refinement. Ialso performed visualization modeling for keyword network relationships, connection degree centrality analysis, and mediation centrality analysis. The results revealed that Mortgage, Dispute, Repair, Case, Response, Condensation, Cost, Institution, Standard, and Valuation are the main keywords that characterize apartment housing defects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.595-602
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• 2020

This study analyzes the plan to increase the social value of the KRC (Korea Rural Community Corporation). For this aim, this study examines the current status of participation in the KRC business and the social value, targeting the farmers among the external stakeholders and derived the main characteristics and important projects of the KRC using network analysis. As a result of network analysis, the rural water management business was found to be the most important business in most regions (Rural Water Development Business 0.805, Agricultural and Fishery Production Base Maintenance Business 0.758, Farmland Banking Business 0.762, Regional Development Business 0.643). On the other hand, in the case of Jeju, the agricultural production base improvement business and the regional development project were found to be the most important projects of KRC due to the unique characteristics of the region. The results of this kind of analysis differ in the importance between KRC business by region, and it is necessary to carefully review the local conditions in order to enhance social value through KRC business in the future. However, since the value of degree centrality between each business is different for each region, efforts to increase the value of KRC's social value, while accounting for local conditions, are needed.

• Journal of Korean society of Dental Hygiene
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• v.23 no.6
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• pp.451-458
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• 2023

Objectives: The purpose of this study is to explore the research trends of elderly oral health through a language network analysis. Methods: A total of 354 published studies with 668 keywords were collected from the Research Information Sharing Service (RISS) between 2000 and 2022. Language network analysis was performed using Textom 6.0, Ucinet 6.774, and NetDraw 2.183. Results: The most frequent keywords were 'elderly', 'oral health', 'quality of life', and 'OHIP-14'. The result of frequency-inverse document frequent keywords showed similar results to the most frequent keywords. The N-gram of keywords shows that 'elderly', 'oral health' (18 times) and 'elderly', 'depression' (7 times). As a results of the analysis of degree centrality and between centrality, 'elderly', 'oral health', and 'quality of life' were found to be high. The CONCOR analysis identified the main clusters of 'quality of life', 'oral health behavior', 'health', and 'oral function disorder'. Conclusions: The results of the current study could be available to know research trends in elderly oral health and it is necessary to improve more comprehensive study in follow-up study.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.68-74
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• 2019

The purpose of this study was to identify research trends of 892 domestic articles (2009-2018) related to emotional labor by using text-mining and network analysis. To this end, the keyword of these papers were collected and coded and eventually converted to 871 nodes and 2625 links for network text analysis. First, network text analysis revealed that the top four main keyword, according to co-occurrence frequency, were burnout, turnover intention, job stress, and job satisfaction in order and that the frequency and the top four core keyword by degree centrality were all relatively the high. Second, based on the top four core keyword of degree centrality the ego network analysis was conducted and the keyword for connection centroid of each network were presented.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.

• Korean Journal of Acupuncture
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• v.40 no.4
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• pp.177-183
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• 2023

Objectives : One of the crucial combinations of acupoints for treating various disorders involves the Eight Confluent acupoints. The present study aims to investigate the selection patterns of the Eight Confluent acupoints in clinical trials and determine the most frequent pairings through network analysis. Methods : The frequencies of the Eight Confluent acupoints were extracted from the Acusynth database, which includes data from 421 clinical investigations. We examined the degree distribution, eigenvector centrality, proximity centrality, and betweenness centrality of these acupoint combinations using network analysis. Results : Data mining revealed that among the Eight Confluent acupoints, PC6 and TE5 were the most commonly applied in the treatment of 30 disorders. Additionally, we identified the most frequently co-occurring pairs of Eight Confluent acupoints by network analysis which included PC6-GV20, SP4-GV4, LU7-LI4, TE5-PC7, GB41-SP6, KI6-BL62, and SI3-BL62. Conclusions : Through the application of data mining and network analysis, we have elucidated the selection patterns and combinations of the Eight Confluent acupoints. These findings provide valuable insights that can enhance doctors' understanding of clinical database-driven Eight Confluent acupoint selection patterns.

• Journal of the Korean Society for information Management
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• v.28 no.4
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• pp.65-83
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• 2011

In this study, Network Text Analysis was performed on 1,752 articles which had been published in recent 7 years and drew the subject concept distribution and their relations in Library and Information Science research areas. Furthermore, for analyzing more recent trends and changing aspects, this study performed secondary analysis based on 482 articles published in recent 2 years. Results show that "public library", and "academic library" concepts were most frequently studied in the field and "evaluation", "education", and "web" concepts showed the highest-degree centrality during the recent 7 years. In the result of recent two years analysis, "web", and "classification" concepts showed high frequency and "user", and "public library" showed an improvement in high degree centrality.

• Child Health Nursing Research
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• v.27 no.3
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• pp.201-210
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• 2021

Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI). Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling. Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life". Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.

• Child Health Nursing Research
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• v.29 no.3
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• pp.182-194
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• 2023

Purpose: This study analyzed research trends in infant and toddler rearing behavior among family caregivers over a 10-year period (2010-2021). Methods: Text network analysis and topic modeling were employed on data collected from relevant papers, following the extraction and refinement of semantic morphemes. A semantic-centered network was constructed by extracting words from 2,613 English-language abstracts. Data analysis was performed using NetMiner 4.5.0. Results: Frequency analysis, degree centrality, and eigenvector centrality all revealed the terms ''scale," ''program," and ''education" among the top 10 keywords associated with infant and toddler rearing behaviors among family caregivers. The keywords extracted from the analysis were divided into two clusters through cohesion analysis. Additionally, they were classified into two topic groups using topic modeling: "program and evaluation" (64.37%) and "caregivers' role and competency in child development" (35.63%). Conclusion: The roles and competencies of family caregivers are essential for the development of infants and toddlers. Intervention programs and evaluations are necessary to improve rearing behaviors. Future research should determine the role of nurses in supporting family caregivers. Additionally, it should facilitate the development of nursing strategies and intervention programs to promote positive rearing practices.