• 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.

• 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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• 2013.08a
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• pp.37-41
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• 2013

본 연구의 목적은 국내 독서치료 주제 연구 문헌을 배출한 학문분야와 주요 연구 내용, 여기에 영향을 미친 문헌의 주제 분야를 도출하고 독서치료 주제 연구 문헌을 바라보는 타 문헌들의 시각을 통해 독서치료 주제 연구 문헌의 성격을 다각적으로 파악하는 것이다. 이를 위해 한국 학술지 인용색인 데이터베이스의 데이터를 활용하여 자아 중심 주제 인용 분석을 실행한 결과 독서치료 연구는 문헌 정보학계의 관련 연구를 토대로 하여 임상적 독서치료를 중심으로 이루어지고 있으며, 문헌정보학 외에 교육학 분야의 연구가 활발하고 유아 정서지능과 영화치료를 주제로 하는 문헌들에 응용되고 있음이 나타났다.