• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.295-312
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• 2012

This research aims to present the ego-centered topic citation analysis, which is a new application of White's ego-centered citation analysis, for analyzing multilayered knowledge structure of a subject domain. An experimental topic citation analysis was carried out on the folksonomy research documents retrieved from Web of Science. Ego-centered topic citation analyses on folksonomy research domain were conducted in three stages: ego-documents set analysis, topic citation identity analysis, and topic citation image analysis. The results showed that the ego-centered topic citation analysis suggested in this study was successfully performed to illustrate the inner and the outer knowledge structures of folksonomy research domain.

• Proceedings of the Korean Society for Information Management Conference
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• 2012.08a
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• pp.153-156
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• 2012

White가 제안한 자아 중심 인용 분석은 연구자를 대상으로 다면적인 분석을 가능하게 하는 방법이다. 이 연구에서는 자아 중심 인용 분석을 연구자 단위가 아닌 연구 주제에 대한 분석으로 응용하는 자아 중심 주제 인용 분석 기법을 제안하고, 시험적으로 폭소노미 주제의 연구문헌 집단에 응용하여 관련 연구의 핵심 문헌들과 주요 적용 이론을 반영하는 인용 정체성과 인용 이미지를 파악해보았다.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.

• Proceedings of the Korean Society for Information Management Conference
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• 2017.08a
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• pp.11-14
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• 2017

딥러닝 연구동향에 대한 계량서지적 분석을 자아 중심 주제 인용분석 기법을 활용하여 시도하였다. 이를 위해서 Web of Science에서 'deep learning'으로 검색된 인용빈도 상위 15건의 논문을 핵심 논문으로 삼고, 이들 핵심 논문 15편을 인용한 논문 집합을 자아 문헌집합으로 삼았으며, 자아 문헌집합들이 인용한 주요 문헌들을 인용 정체성 문헌집합으로 설정하였다. 인용 정체성 문헌집합에 대해 동시인용분석을 실시하여 주요 문헌, 주요 연구 주제를 파악하고, 영향을 끼친 주요 선행 연구를 파악해보았다.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.237-258
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• 2013

As topics of researchers become diverse horizontally or vertically, academic libraries have difficulties to identify the dynamic change of researchers' needs for academic publications. This research aims to illustrate the topic areas of researchers in a department of university by analyzing bibliographies of their publications. First, researchers' publications were used to discover the topic areas where the researchers had published. Second, the cited publications in those papers were analysed to identify the expanded topic areas of these researchers. Finally, highly cited journals were analyzed by network analysis method. The major finding is that the importance of topic areas by the number of journals was not necessarily proportional to that by the number of papers. Researchers have a tendency to use many papers in a small number of journals in a certain topic area. Furthermore, the importance of topic areas discovered by researchers' publications was not the same as that discovered by researchers' citations.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.11-20
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• 2021

The analysis of citing and cited phrases provides an opportunity to enhance search-centric academic information services. However, most current studies focus only on citation analysis among academic associations, researchers, and articles, making it challenging to develop higher citation-based information services. This study proposes citation analysis service methods using citing and cited phrases. First, to verify the feasibility of suggested services, we have collected the most highly cited articles with specific domain terms and followed their citing relationship; after that, we found formal citation types and ratios in the original articles. And we conducted structural analysis, especially with three topics, "Deep Learning," "Green Energy," and "Aging," and then structurally illustrates the citation characteristics of related articles. Finally, we collected four most cited articles and all their citing ones for each subject from Google Scholar and analyzed the ratio of citation types and citation spread. We hope that various citation analysis studies and information services can be further developed based on our discussion for designing better information services.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.379-408
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• 2005

The purpose of this study is to investigate the research trends of library and information science in Korea by means of the subject analysis of the Korean journal articles published during the last sixty years and by means of the ciation analysis of the literatures cited in the journal articles. The results of this study are as follows. First, the subjects of the journal articles are difference from the articles by publication period. The core subjects of the research have been changed over the years. Second, the subjects of library and information science literatures in foreign languages cited in the journal articles are difference from the literatures by citation period and by literature age. Third, the subjects of other disciplinary literatures in foreign langauges cited in the journal articles is difference from the literatures by citation period and by literature age. Fourth, although the half-life of library and information science literatures cited in the journal articles is difference from the literatures by subject, the half-life of the literatures of this discipline is 10-year.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.197-223
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• 2020

In this study, citation-weighted author profiling (CWAP) was developed as a new method that combines the advantages of both author profiling (AP) method and author co-citation analysis (ACA) method. In AP method, words reflect the author's main topics of study. On the other hand, what words reflect in CWAP is topics that the author mainly influences. This enables detailed topic identification, which is the advantage of AP method, and at the same time determines the subjects in which the author has influence, as with ACA method. The proposed CWAP method was applied experimentally to analyze the intellectual structure of school library research in Korea. The results of the trial application revealed in detail what topics each author has a high influence on, and the change of influence over time was also clearly revealed. The CWAP method proposed in this study is expected to be used as a technique to grasp detailed topics from the viewpoint of research influence on which topics the author has been cited for, not as a research productivity perspective of how many papers the author has published.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.13-32
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• 2018

The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

• 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.