• Journal of the Korea Convergence Society
• /
• v.8 no.9
• /
• pp.199-209
• /
• 2017

This study was carried out to confirm a convergent research pattern and researchers' role in stem cell sector by social network analysis. Articles were extracted from 1996 to 2012 in PubMed, 515 authors of 270 embryonic stem cell and induced pluripotent stem cell articles and 1,515 authors of 580 adult stem cell and mesenchymal stem cell articles. Degree(D) and betweenness(B) centrality was measured and co-author network was generated for researcher's role. As a result, Core researcher and Intermediary researcher was identified in co-author network. Core researcher had high D. centrality, otherwise high B. centrality or not. Intermediary researcher for convergent research had high B. centrality and low D. centrality. Conclusively, co-author network will be used as objective data not only to find core researchers in subject area for improving achievement but also to select experts for research project evaluation.

• Journal of the Korean Society for Library and Information Science
• /
• v.57 no.4
• /
• pp.311-331
• /
• 2023

This study attempted to explore the characteristics of knowledge communication and investigate important research topics and key authors by analyzing major academic papers in the field of LIS in Korea for five years from 2018 to 2022. The research method collected and analyzed papers published for five years in four key journals in the field of domestic Library and Information Science from the Korean Citation Index (KCI) database. The paper was selected to extract the author data of the paper and the data of the reference, and network visualization was performed by conducting literature co-citation analysis and author co-citation analysis using Netminer. As a result of the analysis, it was possible to derive a pair of co-citations between authors, and it was confirmed that it is important to include multiple authors in the intellectual structure analysis in the academic field through co-citation frequency analysis among researchers. The literature confirmed the correlation between the topics of the paper, and it was found that research related to Library and Information Science was centered on the topics of library, digital, user, service, and data.

• Journal of the Korean Society for Library and Information Science
• /
• v.40 no.3
• /
• pp.191-214
• /
• 2006

Recently, some bibliometric researchers tried to use the centrality analysis methods and the centrality measures which are standard tools in social network analysis. However the traditional centrality measures originated from social network analysis could not deal with weighted networks such as co-citation networks. In this study. new centrality measures for analyzing bibliometric networks with link weights are suggested and applied to three real network data, including an author co-citation network, a co-word network, and a website co-link network. The results of centrality analyses in these three cases can be regarded as Promising the usefulness of suggested centrality measures, especially in analyzing the Position and influence of each node in a bibliometric network.

• The Journal of Information Systems
• /
• v.30 no.1
• /
• pp.21-44
• /
• 2021

Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

• The Journal of the Korea Contents Association
• /
• v.15 no.10
• /
• pp.387-399
• /
• 2015

Recently collaboration network is generated to find out experts in their field as potential collaborators in health care sector. In this paper, the co-author network of a National Cancer Center researcher was generated for identifying each researcher's role and collaborative research pattern. The co-author network of 2,437 authors was extracted from 1,194 SCI(E) publications from 2000 to 2010 and author's role was analyzed by author's centrality value. Centrality reflecting only the number of papers and centrality weighted by the paper number, impact factor, and authorship contribution was evaluated. On the comparison with simple degree centrality value and the weighted degree centrality, difference of value was statistically significant(t=11.66, p=0.00). Co-author network considering various variables of the paper provides more objective figure of researcher's role. This suggests that co-author network could be more effective in identifying potential collaborators.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.2
• /
• pp.295-301
• /
• 2018

In various disciplines, researchers, not single researchers, tend to cooperate to study the same topic. There are many studies to analyze the collaborative form of various researchers through the social network analysis method, but there are few such studies in the computer field. In this paper, we analyze the characteristics of network and various groups of researchers through the social network analysis technique of the co-authors of the Journal of Korea Institute of Information and Communication Engineering, and analyze the degree centrality, the between centrality and edge weight. As a result of the analysis, many groups were extracted from the co-author's network, but the top 20 groups accounted for more than 50% of the total, also, we could find a pair of researchers who do joint research with a very high frequency. These Co-author networks are expected to be the basis for in-depth research on the subject and direction of research through future researches.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.38 no.2
• /
• pp.1-24
• /
• 2013

The research about customer value has developed over the past years in the marketing field. On the other hand, the stream of the idea has not fully been structured yet. It is the purpose of this research to present the process of development together with the intellectual structure in the field of customer value researches using "Author Co-citation Analysis" (ACA). For the purpose of the research, authors chosen were ranked in order of frequency according to their citations which were used for network analysis. Further, it was of advantage in finding the development process for this research from 1996 to 2011. The trend were set into three time-line groups/trends (1996~2000, 2001~2005, and 2006~2011) that were respectively analyzed. In conclusion, the research represents the intellectual structure of customer value in each period. The research having been tried, influenced a variable field in other marketing researches. While still, many researches limit their focus on a "one-way customer value, used by companies in the past and some in the present, many researches now have a wider perspective about the value and relationship of their customer and their company, together with the society at large.

• The Journal of the Korea Contents Association
• /
• v.22 no.7
• /
• pp.18-29
• /
• 2022

The purpose of this exploratory study is to examine the intellectual structure of data science. For this purpose, this research examined a total of 17,997 bibliographies on data science indexed in Web of Science(WoS) of Clarivate Analytics from 2012 to 2021. This research applied methods such as descriptive analysis, citation analysis, co-author network analysis, co-occurrence network analysis, bibliographic coupling analysis, and co-citation analysis. This research contributes to finding the research directions of future data science topics.

• Journal of Korean Library and Information Science Society
• /
• v.42 no.2
• /
• pp.105-125
• /
• 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 the Korean Society for information Management
• /
• v.31 no.2
• /
• pp.57-77
• /
• 2014

As co-authorship has been prevalent within science communities, counting the credit of co-authors appropriately is an important consideration, particularly in the context of identifying the knowledge structure of fields with author-based analysis. The purpose of this study is to compare the characteristics of co-author credit counting methods by utilizing correlations, multidimensional scaling, and pathfinder networks. To achieve this purpose, this study analyzed a dataset of 2,014 journal articles and 3,892 cited authors from the Journal of the Architectural Institute of Korea: Planning & Design from 2003 to 2008 in the field of Architecture in Korea. In this study, six different methods of crediting co-authors are selected for comparative analyses. These methods are first-author counting (m1), straight full counting (m2), and fractional counting (m3), proportional counting with a total score of 1 (m4), proportional counting with a total score between 1 and 2 (m5), and first-author-weighted fractional counting (m6). As shown in the data analysis, m1 and m2 are found as extreme opposites, since m1 counts only first authors and m2 assigns all co-authors equally with a credit score of 1. With correlation and multidimensional scaling analyses, among five counting methods (from m2 to m6), a group of counting methods including m3, m4, and m5 are found to be relatively similar. When the knowledge structure is visualized with pathfinder network, the knowledge structure networks from different counting methods are differently presented due to the connections of individual links. In addition, the internal validity shows that first-author-weighted fractional counting (m6) might be considered a better method to author clustering. Findings demonstrate that different co-author counting methods influence the network results of knowledge structure and a better counting method is revealed for author clustering.