• Korean Journal of Social Welfare
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• v.68 no.2
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• pp.185-211
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• 2016

This study analyzes key word networks of the papers which are published at Korean Journal of Social Welfare issued by Korean Academy of Social Welfare from 1979 to 2015. It aims at investigating the trends of social welfare researches in Korea by dividing the given period into two: 1979-2000 and 2001-2015. It shows the trends in three ways: methodologies, subjects, and intellectual structures. In order to identify intellectual structure, it calculate centrality indices basing on co-appearance frequency of key words. It also derives some values which explain relationship structure of key words by using pathfinder algorithm, and finally visualizes the intellectual structures by using the NodeXL program. Some implications of the findings of these analyses are discussed in the end.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.29-42
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• 2021

As the low fertility intensifies in Korea, this study investigated fundamental differences between the government's low fertility policy and public perception of it. To this end, we selected four times 'Aging Society and Population Policy' documents and news comments for two weeks immediately after announcement of the third and fourth Policy as analysis targets. Then we conducted word frequency analysis, co-occurrence analysis and CONCOR analysis. As a result of analyses, first, direct childcare support during the first and second periods, and a social structural approach during third and fourth periods were noticeable. Second, it was revealed that both policies and comments aim for the work-family compatibility in 'parenting'. Lastly it was showed public interest in environment of raising children and the critical mind to effectiveness of the policy. This study is meaningful in that it confirmed the public perception using big data analysis, and it will help improve the direction for the future low fertility policy.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.2
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• pp.189-209
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• 2019

Main Path Analysis (MPA) is one of the text mining techniques that extracts the core literature that contributes knowledge transfer based on citation information in the literature. This study applied various text mining techniques to abstract of the paper related with sense-of-place, which is published at Korea and abroad from 1990 to 2018 so that could discuss in a macro perspective. The main path analysis results showed that from 1990, overseas research on sense-of-place has been carried out in the order of personal identity, public land management, environmental education and urban development-related areas. Also, by using the network analysis, this study found that sense-of-place was discussed at various levels in Korea, including urban development, culture, literature, and history. On the other hand, it has been found that there are few topic changes in international studies, and that discussions on health, identity, landscape and urban development have been going on steadily since the 1990s. This study has implications that it presents a new perspective of grasping the overall flow of relevant research.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.431-440
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• 2017

The 2016 Gyeongju Earthquake ($M_L$ 5.8) (occurred on September 12, 2016) and the 2017 Pohang Earthquake ($M_L$ 5.4) (occurred on November 15, 2017) caused unprecedented damages in South Korea. It is necessary to establish basic data related to earthquake-induced mountainous sediment-related disasters over worldwide. In this study, we analyzed previous international studies on the earthquake-induced mountainous sediment-related disasters, then classified research areas according to research themes using text-mining and co-word analysis in VOSviewer program, and finally examined spatio-temporal research trends by research area. The result showed that the related-researches have been rapidly increased since 2005, which seems to be affected by recent large-scale earthquakes occurred in China, Taiwan and Japan. In addition, the research area related to mountainous sediment-related disasters induced by earthquakes was classified into four subjects: (i) mechanisms of disaster occurrence; (ii) rainfall parameters controlling disaster occurrence; (iii) prediction of potential disaster area using aerial and satellite photographs; and (iv) disaster risk mapping through the modeling of disaster occurrence. These research areas are considered to have a strong correlation with each other. On the threshold year (i.e., 2012-2013), when cumulative number of research papers was reached 50% of total research papers published since 1987, proportions per unit year of all research areas should increase. Especially, the proportion of the research areas related to prediction of potential disaster area using aerial and satellite photographs is highly increased compared to other three research areas. These trends are responsible for the rapidly increasing research papers with study sites in China, and the research papers examined in Taiwan, Japan, and the United States have also contributed to increases in all research areas. The results are could be used as basic data to present future research direction related to mountainous sediment-related disasters induced by earthquakes in South Korea.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.137-147
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• 2022

Diagnosis and management of skin condition is a very basic and important function in performing its role for workers in the beauty industry and cosmetics industry. For accurate skin condition diagnosis and management, it is necessary to understand the skin condition and needs of customers. In this paper, we developed SCIS, a big data-based skin care information system that supports skin condition diagnosis and management using social media big data for skin condition diagnosis and management. By using the developed system, it is possible to analyze and extract core information for skin condition diagnosis and management based on text information. The skin care information system SCIS developed in this paper consists of big data collection stage, text preprocessing stage, image preprocessing stage, and text word analysis stage. SCIS collected big data necessary for skin diagnosis and management, and extracted key words and topics from text information through simple frequency analysis, relative frequency analysis, co-occurrence analysis, and correlation analysis of key words. In addition, by analyzing the extracted key words and information and performing various visualization processes such as scatter plot, NetworkX, t-SNE, and clustering, it can be used efficiently in diagnosing and managing skin conditions.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.429-450
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• 2023

The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.

• Journal of Distribution Research
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• v.10 no.3
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• pp.59-86
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• 2005

This study examined whether the efforts of department store for recovering services may be perceived fairly from the standpoint of customers upon any occurrence of service failure, whether such perceived justice contributes to higher customer satisfaction and trust, and whether such customer satisfaction and trust have positive influence on store loyalty of customers, respectively. For this sake, this study investigated relevant literatures, set up some hypotheses to solve main questionable considerations and made a corresponding empirical analysis. For empirical analysis, a questionnaire survey was applied to total 204 customers who experienced in service recovery around domestic major department stores in the last one(1) year. With regard to empirical analysis to verify some hypotheses hereof, this study verified the reliability and validity of each questionnaire item by means of statistical programs like SPSS 10,0 and AMOS 4.0, followed by verifying hypotheses through SEM(structural equation modeling) analysis. These results indicate that positive efforts of department stores for service recovery upon their service failure may bring customer satisfaction and trust in department store, which result in boosting up store loyalty of customers. In this empirical study, it was notably demonstrated that despite any occurrence of service failure, the corresponding efforts of department stores to improve the level of justice perceived by customers in course of service recovery, had positive effects on better customer satisfaction, trust and store loyalty, and these effects induced customer's continuous repurchase, positive WOM(word of mouth) and recommendation about the use of appropriate department store, which may contribute to better its competitive edge.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.163-171
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• 2022

This study was conducted to understand the research trends and central concepts of middle-aged women' health in Korea. For the analysis of this study, target papers published from 2012 to 2021 were collected by entering the keywords of 'middle-aged woman' or 'menopausal woman'. 1,116 papers were used for analysis. The co-occurrence network of key words was developed and analyzed, and the research trends were analyzed through topic modeling of the LSD by dividing it into five-year units (2012-2016, 2017-2021), and visualized word cloud and sociogram were used. The keywords that appeared the most during the last 10 years were obesity, depression, body composition, stress, and menopause symptom. Five topics analyzed in the thesis data for 5 years from 2012 to 2016 were 'postmenopausal self-efficacy and satisfaction enhancement strategy', 'exercise to manage obesity and risk factors', 'intervention for obesity and stress', 'promotion of happiness and life management' and 'menopausal depression and quality of life' were confirmed. Five topics of research conducted for the next five years (2017-2021) were 'menopausal depression and quality of life', 'management of obesity and cardiovascular risk factors', 'life experience as a middle-aged woman', and 'life satisfaction and psychological well-being' and 'menopausal symptom relief strategy'. Through the results, the trend of research topics related to middle-aged women's health over the past 10 years have been identified, and research on health of middle-aged women that reflects the trend of the future should be continued.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.367-387
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• 2024

This study aims to identify the recent trends and intellectual structure of international research in the field of catalog, which is undergoing a major change due to the enactment of new standards and rules and the anticipated future. For this purpose, we collected 680 articles published in the 14 years since 2010 and analyzed 1,942 author keywords extracted from them after preprocessing. The main findings of the analysis are as follows First, overseas cataloging research has seen notable growth since 2017. Second, the most frequent research topics were: cataloging, metadata, RDA, university libraries, authority control, linked data, FRBR, catalog, LCSH, libraries, andonline cataloging. Third, the research themes were divided into two clusters, one related to the traditional aspects of library cataloging and the other related to the more recently discussed topics of authority control, cooperative cataloging, RDA, and linked data, which were further subdivided into 14 subclusters. Fourth, we looked at the growth index and standard performance index of the 14 keyword clusters and found that all but one cluster showed growth in terms of discipline growth. This study is significant in that it can be used as a basis for predicting the future development of inventories for Korean academia and the field and for related education.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.11-39
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• 2018

The study examines the research trends of doctoral dissertations in Library Science and Information Science published in the U.S. for the last 5 years. Data collected from PQDT Global includes 1,016 doctoral dissertations containing "Library Science" or "Information Science" as subject headings, and keywords extracted from those dissertations were used for a network analysis, which helps identifying the intellectual structure of the dissertations. Also, the analysis using 103 subject heading keywords resulted in various centrality measures, including triangle betweenness centrality and nearest neighbor centrality, as well as 26 clusters of associated subject headings. The most frequently studied subjects include computer-related subjects, education-related subjects, and communication-related subjects, and a cluster with information science as the most central subject contains most of the computer-related keywords, while a cluster with library science as the most central subject contains many of the education-related keywords. Other related subjects include various user groups for user studies, and subjects related to information systems such as management, economics, geography, and biomedical engineering.