• Journal of the Korean Society for Library and Information Science
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• v.46 no.4
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• pp.285-309
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• 2012

The purpose of this study is to analyze whether bibliographic factors influence citation speed and the number of citations or not and whether citation speed affects the number of citations. Another purpose of this study is that if bibliographic factors carry out a significant role. For this analysis, this study is based on the assumption that all papers published by researchers in South Korea distributed power law shape. The main results of this study are as follows: First, the papers written by foreign first authors or reprint authors were cited more quickly from first citation speed and average citation speed. These papers were cited much more from first citation speed and average citation speed than by domestic first authors or reprint authors. The papers, collaborated by international researchers, were cited more quickly from first citation speed but were not different from average citation speed than by only domestic researchers. The papers, collaborated by international researchers, were cited much more than by only domestic stand-alone researchers. The number of authors and the impact factor influenced first citation speed, average citation speed and the number of citations. Second, the faster first citation speed and the slower average citation speed, the more papers were cited. First citation speed more affected the higher number of citations than the average citation speed. Third, all five bibliographic factors influenced the impact relationship from first citation speed to the number of citations through the moderating effect analysis. Fourth, only three bibliographic factors (the country of the first author; the country of the reprint author; the number of the coauthors) affected the impact relationship from first citation speed to the number of citations but two bibliographic factors did not influence through the moderating effect analysis.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.117-122
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• 2022

최근 국내외 ESG 연구가 활발해지고 있는 가운데, ESG 연구는 급격한 양적 성장을 하고 있음에도 학술지의 질적 수준을 평가할 수 있는 계량적인 논문은 부족한 상태이다. 본 연구는 한국학술지인용색인(KCI)에서 경영학 분야 내의 KCI 인용지수를 활용하여 상위 10개의 학회를 선정하고 이들 간의 ESG 논문 인용빈도와 네트워크 분석을 하였다. 상호 인용빈도를 활용하여 연결망을 작성하고 네트워크 분석 관점에서 ESG 주제에 관한 각 학술지 간 상호인용빈도를 통해 주어진 학술지의 영향력지수(Impact Factor)와 중심성 지수를 기초하여 연구하였다. 이러한 연구를 바탕으로 학술지들이 핵심 문헌을 식별하고 학문 내 지적 구조를 규명하여 경영학 분야의 ESG 연구 동향을 파악하고자 한다. 본 연구는 국내 발간된 경영학 학술지의 ESG에 대한 학술지의 영향력 인용지수를 비교해 보고 나아가 경영학 학술지의 자기 인용 비율을 확인하고 경영학뿐만 아니라 타 학문 분야에서 경영학 관련 학술지에 대한 인용이 이루어질 수 있도록 다학제적 교류와 추가 연구의 필요성을 제기하고자 한다.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.115-134
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• 2012

The author co-citation analysis is generally based on the frequency of the first author because most citation databases include only the first author in the bibliographic information. In this sense, the purpose of this study is to provide a better knowledge structure by utilizing the multiple authorship of author co-citation analysis. To achieve the purpose of this study, four different data sets are prepared: (1) counting the first author, (2) counting all the author without limiting the total frequency, (3) counting all the author with limiting the total frequency, and (4) counting adjusted frequencies based on the order of author subscription. The findings of this study show that there are clear differences between the knowledge structure counting all the author and the one counting only the first author. In addition, depending on the different methods, there are subtle changes of cluster members for authors.

• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.273-296
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• 2013

The purpose of this study is to examine the data coverage and citation threshold for analyzing SPLC(Search Path Link Count) as a main path of a historiograph of a certain topic in order to provide 'core' papers of global research trends to a researcher affiliated with a local R&D institution. 5 datasets were constructed by retrieving and collecting 2,318 articles on RGB LED on Web of Science published from 1990-2013 and 20,109 articles which cited these original 2,318. The SPLC analysis was performed on each dataset by increasing the threshold of citation counts, and the changes and resilience of the 28 extraced networks were compared. The results of user feedback on 198 unique core papers from 28 SPLC networks received from LED researchers affiliated with a Korean government-sponsored research institution were also analyzed. As a result, it is found that the nodes in each SPLC network in each dataset were differentiated by the citation counts, while the changes in the structure of SPLC networks were slight after the networks' citation counts were set at 40. Additionally, the user feedback showed that personalized research interest generally matched to the global research trends identified by the SPLC analysis.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.205-221
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• 2015

The impact of a journal is commonly used as the impact of an individual paper within that journal. It is problematic to interpret a journal's impact as a single paper's impact of the journal, so there are several researches to measure a single paper's impact with its own citation counts. This study applied 8 impact indicators to Korean Citation Index database and examined discipline bias of each indicator. Analyzed indicators are simple citation counts, PageRank, f-value, CCI, c-index, single publication h-index, single publication hs-index, and cl-index. PageRank has the least discipline bias at highly ranked papers and journal bias in a discipline. On the contrary, simple citation counts showed strongly biased results toward a certain discipline or a journal. KCI database provides only simple citation counts. It needs to show PageRank (global indicator) to discover influential papers in diverse areas. Furthermore it needs to consider to provide the best of local indicators. Local indicators can be calculated only with papers in users' search results because they uses citation counts of citing papers and the number of references. They are more efficient than global indicators which explore the whole database. KCI should also consider to provide Cl-index (local indicator).

• Journal of Korean Library and Information Science Society
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• v.51 no.2
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• pp.273-294
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• 2020

The purpose of this study is to provide an in-depth analysis on the publication patterns of the 1,029 journal articles by the Life Sciences' faculty at the K University, for the years 2004-2017 and to investigate any difference between their publication patterns and the citedness for the years 2004-2018. Among the three funding agency types, the research publications supported by foreign funding received the more citations than publications by other types of funding, and the study also found a statistical difference in the citedness (F = 10.467, p < .000***). In addition, the internationally co-authored publications received more citations than three other types of co-authored publications in terms of the immediacy index per publication and the average citations per publication.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.283-308
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• 2008

In this study, we testify that network structural attributes of a citation network can explain other aspects of journal citation behaviors and the importances of journals. And we also testify various citation impact indicators of journals including JIF and h-index to verify the difference among them especially focused on their ability to explain an institution's local features of citation behaviors. An institutional citation network is derived using the articles published in 2006-2007 by biotechnology faculties of Y University. And various journal citation impact indicators including JIF, SJR, h-index, EigenFactor, JII are gathered from different service sites such as Web of Science, SCImago, EigenFactor.com, Journal-Ranking.com. As a results, we can explain the institution's 5 research domains with inter-citation network. And we find that the co-citation network structural features can show explanations on the patterns of institutional journal citation behavior different from the simple cited frequency of the institution or patterns based on general citation indicators. Also We find that journal ranks with various citation indicators have differences and it implies that total-based indices, average-based indices, and hybrid index(h-index) explain different aspects of journal citation pattern. We also reveal that the coverage of citation DB doesn't be a matter in the journal ranking. Analyzing the citation networks derived from an institution's research outputs can be a useful and effective method in developing several library services.

• 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.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.23-33
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• 2021

This study analyzed news articles about 'Young-Kl' reported by 11 media outlets, identifying news frames and quotation frames. Using a semantic network analysis, this study inspected the quotations frames and measured the frequency of the quotes and sources types. Also, the concentration index of the frames was measured. The results showed that news frames consisted of 10 topics and quotation frames consisted of 14 topics. Although the differences among quotation frames by media as well as by source types were observed, the concentration index of sources such as government, political arena, and business appeared high. Therefore, this study suggested that numerical diversity of news sources would not establish the diversity of news frames.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.1-15
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• 2022

This study analyzes the relationship of citations appearing in the patent data to understand knowledge transfers and impacts between patent documents in the field of pharmaceutical research. Patent data were collected from a website, Google Patents. The top 25 assignees were selected by searching for patent documents related to pharmaceutical research. We identify the citation relationships between assignees, then calculate and compare the values of h-index and derived indicators by using the number of citations and rank for each document of each assignee. As a result, in the case of pharmaceutical research, the assignee, such as 'Pfizer, MIT, and Abbott' shows a high impact. Among the five bibliometric indicators, the g-index and hS-index show similar results, and the indicators are the most related to the rankings of Total Citation Frequency, Cites per Patents, and Maximum Citation Frequency. In addition, it is highly related to the five indicators in the order of Total Citation Frequency, Cites per Patents, and Maximum Citation Frequency. In some cases, it is difficult to make an accurate comparison with Cites per Patents alone, which is previously known to indicate the technological influence of patent assignees.