• 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.

• Information and Communications Magazine
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• v.31 no.11
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• pp.46-51
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• 2014

최근 정보통신 기술의 발전과 더불어 급성장 중인 소셜 네트워크는 개인 혹은 집단간의 실제 사회적 관계를 네트워크 구조로 반영하고 있다. 소셜 네트워크를의 구조를 보다 정확하게 이해하고 소셜 네트워크 내에서 정보가 전파되는 패턴을 파악하기 위해 소셜 네트워크를 수학적으로 모델링하고, 이를 응용하여 소셜 네트워크 빅 데이터를 분석하는 다양한 연구가 이루어지고 있다. 본고에서는 소셜 네트워크의 구조 분석과 정보 확산 패턴 파악에 관한 주요 연구 사례들을 소개하고, 특히 소셜 빅 데이터 분석과 관련된 연구 주제 및 응용 사례들을 살펴보고자 한다.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.141-157
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• 2021

In this study, we aimed to understand research trends of domestic artificial intelligence research. To achieve the goal, we applied network analysis and dynamic topic modeling to domestic research papers on artificial intelligence. Among the papers that have been indexed in KCI (Korean Journal of Citation Index) by 2020, metadata and abstracts of 2,552 papers where the titles or indexed keywords include 'artificial intelligence' both in Korean and English were collected. Keyword, affiliation, subject field, and abstract were extracted and preprocessed for further analyses. We identified main keywords in the field by analyzing keyword co-occurrence networks as well as the degree and characteristics of research collaboration between domestic and foreign institutions and between industry and university by analyzing institutional collaboration networks. Dynamic topic modeling was performed on 1845 abstracts written in Korean, and 13 topics were obtained from the labeling process. This study broadens the understanding of domestic artificial intelligence research by identifying research trends through dynamic topic modeling from abstracts as well as the degree and characteristics of research collaboration through institutional collaboration networks from author affiliation information. In addition, the results of this study can be used by governmental institutions for making policies in accordance with artificial intelligence era.

• Korean Journal of Comparative Education
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• v.28 no.1
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• pp.1-24
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• 2018

The objective of the article is to find the research trends and the main traits presented in the keywords on abstracts of research articles of "International Journal of Education Development" from 2002 to 2017. To do this, Text Network Analysis(TNA) was applied targeting 966 papers on the journal and the major research outcomes are as follows. First, the frequency analysis on the keywords showed that the keywords like Administration of education program, Schools and instruction, Regional public administration, Educational support service, Elementary education, and Elementary and secondary school were analyzed more than 100 times and also high in centrality degree. Second, the analysis results of the keywords presented in those research articles by development goal periods showed that several new keywords like Elementary education, Elementary and secondary school, Education quality, Secondary education, Educational planning have emerged frequently after SDGs and these keywords showed high in their centrality analysis. Third, the analysis on education level showed that the keywords like Elementary education, Administration of education program, School children were high in frequency and centrality degree in Elementary level. In secondary level, Schools and instruction, Administration of education program, Academic achievement were high, and in high level, college and university was high, respectively.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.221-238
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• 2020

This study aims to investigate the scholarly communications and citation influences in library and information science field by conducting journal citation network analysis. For data collection, four major journals in library and information science field were chosen and 4,471 of research papers and 18,424 of citation records were collected from Korean Citation Index. The results show that Journal of the Korean Society for Library and Information Science was the most influential journal with highest citation in LIS fields, while Journal of the Korean Society for Library and Information Science Management influenced other research fields.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.81-97
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• 2022

This paper's purpose is to get hold of the recent research trend by analyzing the variables uesd in startups related papers. The startups related papers in this paper are the papers which include 'startups' in the title of the registered papers from the year 2013 to the year 2020. This study's analysis methods are text-mining of all variables and text-network analysis of affected variables. Visualizing tool for network analysis is Gephi. The result of variables' analysis is as follows. First, independent variables consist mainly of variables about startups' internal factors and outside environment, but due to startups' features like early stage company's features, innovative features, most of variables are about enterprise internal competitiveness, marketing 4P strategy, entrepreneurship, coopreation method, transformational leadership, enterprise features, lean startup strategy, enterprise internal communication, value orientation, task conflict, relationship conflict, knowledge sharing, etc. Second, dependent variables are mainly about outcome, and are classified into financial performance and non-financial performance by overall concept. In other words, startups related papers have higher interest in non-financial performance, like management performance, team performance, SCM performance as well as financial performance like sales quantity owing to startups' immaturity in getting good financial performance. Through this study we can find out as follows. Although there are not many officially registered papers dealing with startups, those papers include various themes about stratups. For example, there are trendy themes like lean startups strategy, crowdfunding, influencer and accelerator, etc.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2006.05a
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• pp.211-216
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• 2006

교통주제도는 건설교통부와 한국교통연구원이 ${\ulcorner}$국가교통DB구축사업${\lrcorner}$의 일환으로 제작한 것으로, 국토지리정보원의 NGIS 수치지도(축척 1:5,000)를 기반으로 하여 현장조사 및 문헌조사를 통해 갱신, 보완하여 교통 분야의 활용에 적합하도록 구축한 GIS 수치지도이다. 교통주제도는 현장조사와 문헌조사를 통해 수집된 자료를 기반으로 구축되며 이중 교통시설물조사는 문헌자료(준공도로현황 등)를 참고하여 산정된 조사대상에 대하여 GPS 조사시스템을 활용, 도형 및 속성정보를 취득하는 것을 말한다. 조사항목은 도형정보(노드, 링크) 및 속성정보(차선수, 도로번호 등)이며 GPS 조사시스템과 조사원장(도면)을 이용하여 조사한다. 교통시설물조사와 문헌자료조사를 통해 수집된 자료는 단위도엽(1:5,000기준)별로 교통주제도에 반영되며 최종적으로 전국단위의 통합자료로 구축된다 교통주제도는 사용목적과 축척기준에 따라 단순화되며 이를 교통주제도 레벨이라 한다. 교통주제도의 레벨은 총 4단계로 구분되며 현재 레벨2에서 레벨4까지 구축되고 있다. 교통분석용 네트워크는 교통시설투자계획, 수요분석, 타당성 평가와 같은 교통분야의 연구를 수행하기 위해 반드시 필요한 자료이다. 교통분석용 네트워크는 교통주제도보다 더 단순화된 도로망 모델로서 구성요소는 노드(시점, 종점, 죤 센트로이드)와 링크(도로망, 센트로이드 커넥터)이며 도로의 기하구조보다는 논리적 구조(방향성, 노드/링크 연결성 등)에 중점을 둔 데이터이다 교통분석용 네트워크는 교통주제도의 도형과 속성정보를 기반으로 하며 각종 통계자료(도로교통량통계연보 등)를 활용, 구축된다. 교통분석용 네트워크는 구축시점에 따라 현재 및 장래 네트워크로 구분되며 장래 네트워크는 기준년도부터 2031년까지 5년 단위로 계획된 장래도로를 반영하여 구축된다. 교통주제도 및 교통분석용 네트워크는 국가교통DB구축사업을 통해 구축된 자료로서 교통체계효율화법 제9조의4에 따라 공공기관이 교통정책 및 계획수립 등에 활용할 수 있도록 제공하고 있다. 건설교통부의 승인절차를 거쳐 제공하며 활용 후에는 갱신자료 및 활용결과를 통보하는 과정을 거치도록 되어있다. 교통주제도는 국가의 교통정책결정과 관련분야의 기초자료로서 다양하게 활용되고 있으며, 특히 ITS 노드/링크 기본지도로 활용되는 등 교통 분야의 중요한 지리정보로서 구축되고 있다.

• Journal of vocational education research
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• v.33 no.3
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• pp.83-104
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• 2014

The study examined the trends of research on Meister high schools in Korea. The study also investigated differences of research interests between the university faculty and graduate students who are the future researchers in this field. A total of 56 research articles were analyzed using the network text analysis method and the content analysis. The results showed that 56% of all studies was done to reveal the distinguishable characteristics of Meister students and teachers compared to their counterpart in vocational schools. 17.6% of studies were about school curriculum, while 14.0% of studies were on school organization and operation. Only 12.3% of studies were conducted to evaluate school performance. Quantitative studies outnumbered qualitative ones. Based on the results, this study suggested implications for policies and future research on meister high school.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.247-267
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• 2011

The purpose of this study is to investigate knowledge structure of knowledge organization research area in Korea. The study employed content analysis and network analysis to analyze degree centrality, betweenness, and eigenvector as well as frequency of words. It also analyzes research articles published during the period of 2000-2001. The study can be summarized that the network of keywords of knowledge organization researches is compact and complicated. Cataloging and classification play important roles in the network, and metadata and ontology becomes focal areas in knowledge organization. On the other hand, networks of authorships and authors are broad and fragmented. Collaboration is not active enough.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.53-84
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• 2016

This study clarified the intellectual structure of international collaboration in psychiatry based on analyzing networks in order to vitalize for international collaboration in psychiatry in South Korea. The data set was collected from Web of Science citation database during the period from 2009 to 2013. SU="psychiatry" search formulary (means field of psychiatric medical research) was used through advanced retrieval function and a total of 18,590 articles were selected among international collaborations. A total of 85 different keywords were selected from the 18,590 articles, and the results of analysis were as follows. First, this study examined 8 sub-subject areas focusing on disorders, and found that major subject areas could be divided into a total of 8 sub-subject areas. Second, this study examined 6 keywords that have a strong impact, and extend subject areas by promoting intermediation between other keywords Third, this study examined sub-subject areas by using the Knowledge Classification Scheme of the National Research Foundation of Korea through community analysis, and found a total of 15 clusters and a total of 12 sub-subject areas.