• Journal of Korean Library and Information Science Society
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• v.42 no.2
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• pp.105-125
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• 2011

This paper grasps about various features of the coauthorship network based on the co-author frequency in the Korean LIS Research Community. This issue includes many topics such as changable aspects of coauthorship network, properties of higher cooperative authors groups. This work is mostly analyzed through a bibliographic analysis of articles which is published from 2000 to 2009(10 years) in Korean Library & Information Science major four journals. The results show three major implications. 1) There is a various structural changes of coauthorship network on the change of the co-author frequency. 2) There are 21 research pairs in the higher cooperative authors groups with the co-author frequency more than five. 3) There seems that any subjective relations between the articles which is produced by 21 research pairs were not clearly presents.

• Journal of Korean Library and Information Science Society
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• v.41 no.2
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• pp.297-315
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• 2010

This study investigates the various statistical data and measures of coauthorship network in the Korean LIS Research Community such as patterns of coauthorship, structural properties, types of cluster, centrality & impact analysis. This issues are mostly addressed through a Social Network Analysis of articles published from 2000 to 2009(10 years) in Korean Library & Information Science major four Journals. The coauthorship network was constructed and various measures of four centralities, PageRank, Effect size were calculated. The results show three implications. 1) There presents a phenomenon of Pareto's law in the articles publishing counts. 2) The top authors based on publishing counts prefer co-work publishing than solo-publishing. 3) The counts of article publishing are significantly correlated with five measures of network and not correlated with the case of power centrality.

• Journal of Information Science Theory and Practice
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• v.2 no.2
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• pp.6-15
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• 2014

Initial based disambiguation of author names is a common data pre-processing step in bibliometrics. It is widely accepted that this procedure can introduce errors into network data and any subsequent analytical results. What is not sufficiently understood is the precise impact of this step on the data and findings. We present an empirical answer to this question by comparing the impact of two commonly used initial based disambiguation methods against a reasonable proxy for ground truth data. We use DBLP, a database covering major journals and conferences in computer science and information science, as a source. We find that initial based disambiguation induces strong distortions in network metrics on the graph and node level: Authors become embedded in ties for which there is no empirical support, thus increasing their sphere of influence and diversity of involvement. Consequently, networks generated with initial-based disambiguation are more coherent and interconnected than the actual underlying networks, and individual authors appear to be more productive and more strongly embedded than they actually are.

• Journal of Korea Technology Innovation Society
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• v.10 no.4
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• pp.605-628
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• 2007

We analyze the embedded structure of the cooperative research network of innovation studies in Korea by employing the social network methodology. The network covers all the contributing authors of two journals such as JTI and KTIS, which are the representative journals in the area. Across the networks, the following is noted: networks are highly segmented and the link density is low. However, the KTIS network contains a huge component with 131 authors which implies the existence of a strong cooperative research infrastructure. We derived three sub-networks such as technology economics, technology management, and technology policy. The technology policy network has the lowest link density, while the technology management network of KTIS shows relatively high cohesion among the researchers. Simulation analysis for the mean links of networks by author affiliation divided into university and others show no significant difference between the two networks. We also found a higher ratio of linkage within affiliated network than between networks, rejecting our hypothesis that researchers will not discriminate their research partners due to strong governmental inducement of academia-res each-industry cooperation. The explainability of indices from network structure such as structural holes and clustering coefficients on the performance of researchers measured by the number of citations confirms the results reported in Oh, Choi & Kim (2006) which dealt with the research network of information systems.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.3
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• pp.63-87
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• 2023

The study aims to investigate research trends in the UK records management field and compare the results with domestic research by analyzing research articles published in Archives and Records for the UK's research trends and The Korean Journal of Archival Studies (KJAS) for domestic ones. The study analyzed 318 articles published in KJAS and 142 articles published in Archives and Records since 2013, when the journal changed its title from Journal of the Society of Archivists, to investigate the distribution of authors, including the ratio of coauthorship and authors' affiliations. A set of 1,251 unique terms were extracted from KJAS, and 508 unique terms were extracted from Archives and Records for keyword co-occurrence network analyses. The result shows that the main research topics for KJAS include studies on (1) records management in general, such as archives, records, records management, and archival information service, (2) public records management, (3) personal or private records management, and (4) the techniques for records management, such as archival appraisal, selection, and disposition. In Archives and Records, (1) there are several case studies related to community and local archives, and (2) studies related to records management techniques, such as records description, appraisal, access, preservation, and service, have been performed continuously; furthermore, (3) studies on the digitization of oral history and audiovisual records are also one of the most researched areas.

• Radiation Oncology Journal
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• v.29 no.3
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• pp.164-173
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• 2011

Purpose: This research aimed to analyze the patterns of co-authorship network among the Korean radiation oncologists and to identify attributing factors for the formation of networks. Materials and Methods: A total of 1,447 articles including contents of ‘Radiation Oncology' and 'Therapeutic Radiology' were searched from the KoreaMed database. The co-authorship was assorted by the author's full name, affiliation and specialties. UCINET 6.0 was used to fi gure out the author's network centrality and the cluster analysis, and KeyPlayer 1.44 program was used to get a result of key player index. Sociogram was analyzed with the Netdraw 2.090. The statistical comparison was performed by a t-test and ANOVA using SPSS 16.0 with p-value < 0.05 as the significant value. Results: The number of articles written by a radiation oncologist as the first author was 1,025 out of 1,447. The pattern of coauthorship was classified into five groups. For articles of which the first author was a radiation oncologist, the number of singleauthor articles (type-A) was 81; single-institution articles (type-B) was 687; and multiple-author articles (type-C) was 257. For the articles which radiation oncologists participated in as a co-author, the number of single-institution articles (type-D) was 280 while multiple-institution articles (type-E) were 142. There were 8,895 authors from 1,366 co-authored articles, thus the average number of authors per article was 6.51. It was 5.73 for type-B, 6.44 for type-C, 7.90 for type-D, and 7.67 for type-E (p = 0.000) in the average number of authors per article. The number of authors for articles from the hospitals published more than 100 articles was 7.23 while form others was 5.94 (p = 0.005). Its number was 5.94 and 7.16 for the articles published before and after 2001 (p = 0.000). The articles written by a radiation oncologist as the first author had 5.92 authors while others for 7.82 (p = 0.025). Its number was 5.57 and 7.71 for the Journal of the Korean Society for Therapeutic Radiology and Oncology and others (p = 0.000), respectively. Among the analysis, a significant difference in the average number of author per article was indicated. The out-degree centrality of network among authors was 4.26% (2.03-7.09%) while in-degree centrality was 1.31% (0.53-2.84%). The three significant nodes were classified and listed as following: Choi, Eun Kyung for 1991-1995, Kim, Dae Young for 1998-2001, Park, Won and Lee, Sang Wook for 2003-2010. Choi, Eun Kyung and Kim, Dae Young appeared in two cases, and ranked as the highest degree in centrality. In the key player analysis, Choi, Eun Kyung and Lee, Sang Wook appeared in two cases, and ranked as the highest. From the cluster analysis, Sungkyunkwan University, Seoul National University and Yonsei University revealed as the three large clusters when Ulsan University, Chonnam National University, and Korea Institute of Radiological & Medical Science as the medium clusters. Conclusion: The Korean radiation oncologist's society shows a closed network with numerous relationships among the particular clusters, and the result indicates it is different from other institutions in the pattern of co-authorship formation of the major hospitals.

• 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.