• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.149-154
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• 2017

Objectives: The purpose of this study is to analyze the co-author networks in the Journal of the Korean Academy of Child and Adolescent Psychiatry, a representative journal published by a branch of the domestic psychiatric academy, in order to present the current state of the co-authoring of and developments in child and adolescent psychiatry. Methods: We visualized and estimated the basic characteristics of the co-author networks shown by 564 authors who wrote 251 papers published in the Journal of the Korean Academy of Child and Adolescent Psychiatry between 2005 and 2015, in order to assess their network characteristics, author centrality, and relevance to research performance. Results: The co-author networks in the Journal of the Korean Academy of Child and Adolescent Psychiatry showed the characteristics of a small world and scale-free network. There was a correlation between the author centrality within the network and the research performance of the authors, but less correlation was shown between the centrality and mean paper citation counts. Conclusion: The network structure in the Journal of the Korean Academy of Child and Adolescent Psychiatry showed similarity to the co-authoring of other branches. However, given that the mean paper citation counts were less correlated with the author centrality than those in other branches, it may be necessary to promote an increase in the mean paper citation counts.

• Journal of Preventive Medicine and Public Health
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• v.41 no.1
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• pp.1-9
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• 2008

Objectives : This study evaluated knowledge structure and its effect factor by analysis of co-author and keyword networks in Korea's preventive medicine sector. Methods : The data was extracted from 873 papers listed in the Journal of Preventive Medicine and Public Health, and was transformed into a co-author and keyword matrix where the existence of a 'link' was judged by impact factors calculated by the weight value of the role and rate of author participation. Research achievement was dependent upon the author's status and networking index, as analyzed by neighborhood degree, multidimensional scaling, correspondence analysis, and multiple regression. Results : Co-author networks developed as randomness network in the center of a few high-productivity researchers. In particular, closeness centrality was more developed than degree centrality. Also, power law distribution was discovered in impact factor and research productivity by college affiliation. In multiple regression, the effect of the author's role was significant in both the impact factor calculated by the participatory rate and the number of listed articles. However, the number of listed articles varied by sex. Conclusions : This study shows that the small world phenomenon exists in co-author and keyword networks in a journal, as in citation networks. However, the differentiation of knowledge structure in the field of preventive medicine was relatively restricted by specialization.

• Health Policy and Management
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• v.18 no.2
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• pp.86-106
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• 2008

This research analyzed. knowledge structure and its effect factor by analysis of co-author and keyword network in Korea's health policy and administration sector. The data was extracted from 339 articles listed in the Korean Journal of Health Policy and Administration, and was transformed into a co-author and keyword matrix. In this matrix the existence of a link was defined by impact factors which were calculated by the weight value of what the role was and the rate of how many authors contributed. We demonstrated that the research achievement was dependent on the author's status and network index. Analysis methods were neighborhood degree, correspondence analysis, multiple regression and the difference of weight distribution by research fields. Co-author networks were developed as closeness centrality as well as degree centrality by a few high productivity researchers. In particular, power law distribution was discovered in impact factor and research productivity. The effect of the author's role was significant in both the impact factor calculated by the participatory rate and the number of listed articles. Especially, this journal shared its major researchers who had a licensed physician with the Journal of Preventive Medicine and Public Health. Therefore, social scientists were likely to be small co-author network differently from natural scientists. It was so called 'two cultures' phenomenon. This study showed how can we verified academic research structure existed in the unit of journal like as citation networks. The co-author networks in the field of health policy and administration had more differentiated and clustered than preventive medicine and epidemiology fields.

• Journal of Korean Library and Information Science Society
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• v.44 no.3
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• pp.405-428
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• 2013

This study tried to explore the relation between research networks(coauthor network, author co-citation network, author bibliographic coupling network) and research performance of Records and Archives Management study in Korea. For the analysis, three basic types of network centrality and three indicators of research performance are used. The summary of this study is as follows: Firstly, there are relations between three centralities and three indicators of research performance in the coauthor network. Secondly, there are relations between betweenness centrality and research performance in the author co-citation/author bibliographic coupling networks. Thirdly, there are relations between three centralities in the each research network. Fourthly, there are not high relations between all centralities of the three research networks.

• Journal of Information Technology Services
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• v.13 no.4
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• pp.93-107
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• 2014

Interests on collaborative research and academic relationship among researchers have been increased. Collaborative researchers can maximize productivity, time and cost savings, and reduce the risk of research. An empirical study on the research productivity of co-authors' network and review efficiency of the reviewer network was conducted based on co-author networks and reviewer networks in Korea Society of IT Service. This study aims to find the characteristics of the co-author and reviewer networks, and to analyze research productivity and review efficiency in order to draw some implications. The meaning of interactions among professional groups was analyzed. Research productivity index was calculated using 728 authors' papers submitted to the society. In order to verify the effects of indicators of social network analysis on research productivity and review efficiency, correlation and regression analyses were used. As a result, the indicators of network centrality did not affect the review efficiency, but affect the research productivity.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.288-296
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• 2012

The method proposed by the author is intended for assistance in decision-making (concerning changes of connections) by operators of complex distribution systems during states of malfunction (particularly in the events of malfunctions, for which the consequences encompass extended parts of the network), through designation of connection action scenarios (creating substitute configurations). It is the use by the classifying system working with the co-evolution algorithm that enables the effective creation of substitute scenarios for the Medium Voltage electric power distribution network. The author also completed works concerning the possibility of using cooperation of the evolutionary algorithm and the co-evolutionary algorithm with local search algorithms. The method drawn up may be used in current systems managing the work of distribution networks to assist network operators in taking decisions concerning connection actions in supervised electric power systems.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.3
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• pp.191-214
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• 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 Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1259-1270
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• 2011

This study analyzed an aspect of co-author relationship in papers published in the Korean Journal of Applied Statistics by social network analysis. The data were extracted from 664 papers in the journal from 2000 to 2010. Authors at center of the network are detected by a network centrality analysis. Sub-network analysis found distinguishable research groups from the point of view of their topics or affiliations. The significance of affiliations to co-author relationship was examined by logistic regression analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.295-301
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• 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 Society for information Management
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• v.31 no.2
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• pp.57-77
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• 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.