• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.420-428
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• 2010

The advancement of the Science for complex systems enables the analysis of many social networks. We constructed and analyzed a Korean movie star network as one of social networks, based on the 100 Korean movie selection for a main data source. Until now, the research trend has been the structural analysis of network, focused on link numbers, such as degree, betweenness and clustering coefficient. But it is time that the research is not limited by the structural analysis of networks only. Rather, the research goal should be aimed to an information analysis, performed by identifying and analyzing central modules that are regarded as the core of complex networks, using k-core analysis method. In this research, we constructed a network of movie stars who have appeared in 100 Korean movie selection, provided by Korean movie database, also we analyzed its core modules with and without weights, and the trend of seasonal expansion of the network. We expect our findings can be used as the basic data applicable to a model for understanding of the expansion and evolution of networks.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.96-104
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• 2020

As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.981-993
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• 2018

Smart healthcare is convergence of ICT and healthcare services, and interdisciplinary research has been actively conducted in various fields. The objective of this study is to investigate trends of smart healthcare research using topic modeling and ego network analysis. Text analysis, frequency analysis, topic modeling, word cloud, and ego network analysis were conducted for the abstracts of 2,690 articles in Scopus from 2001 to April 2018. Topic Modeling analysis resulted in eight topics, Topics included "AI in healthcare", "Smart hospital", "Healthcare platform", "Blockchain in healthcare", "Smart health data", "Mobile healthcare", " Wellness care", "Cognitive healthcare". In order to examine the topic modeling results core deeply, we analyzed word cloud and ego network analysis for eight topics. This study aims to identify trends in smart healthcare research and suggest implications for establishing future research direction.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.69-76
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• 2002

In conducting studies related to the national base networks, it is very important to construct a simulation network. This research provides an algorithm to construct the simulation network from the digital transportation map which is constructed based on the National Geographic Information System(NGIS). The algorithm consists of three functions(extraction of networks from transportation digital map, transform of the derived network into one suitable to transportation simulation model, and inspection of errors in the network). The direct derivation of a simulation network from GIS enables to enhance the reliability of an analysis related to a transportation facility investment as well as to reduce cost and time. In this research, Emme/2 which is generally accepted transportation planning fields is adapted for the target system. However, this algorithm will be extended to other simulation models such as Satong-Paldal which is the only transportation simulation model developed in Korea, and Tranplan in the near future.

• 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 Korea Technology Innovation Society
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• v.15 no.2
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• pp.369-399
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• 2012

Purpose: Health technology research & development is an important area to leading future. This study examined the current trends for 'oncogene' based on the research subject network to deduce a research front. Method: Papers were extracted from PubMed database using MeSH term for studies on 'oncogenes' and further categorized as papers published by Korean. Keywords were collected from all of articles. Research subject network was generated by keywords. Research subject network was analyzed by weighted degree centrality based social network analysis and transition of research subjects was analyzed by the time series. Results: On 'oncogenes', 'Genes, ras', 'Apoptosis', 'Signal Transduction' had a high degree centrality and currently 'Antineoplastic Agents', 'Prognosis', and 'Tumor Markers, Biological' were widely conducted. Conclusion: Consistency of research trend pattern was found by analyzing oncogene network with compromised to international vs. domestic trends. Analyzing keyword networks in various subject area, those will allow us to predict the research progress and propose evidence of research & developmental strategy.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.635-648
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• 2006

As the advances of Internet infra structure and the support of console and mobile for network games, the industry of online game has been growing rapidly, and the online game traffic in the Internet has been increasing steadily. For design and simulation of game network, the analysis of online game traffic have to be preceded. Therefore a number of papers have been proposed for the purpose of analyzing the traffic data of network games and providing the models. We make and use GameNet Analyzer as a dedicated tool for game traffic measurement and analysis in this paper. We measure the traffic of FPS Quake 3, RTS Starcraft and MMORPG World of Warcraft (WoW), and analyze the packet size, packet IAT(inter-arrival time), data rate and packet rate according to the number of players and in-game behaviors. We also present the traffic models using measured traffic data. These analysis and models of game traffic can be used for effective network simulation, performance evaluation of game network and the design of online games.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.169-190
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• 2021

Research in various academic fields using network analysis techniques has been conducted and grown. This study performed bibliographical analysis and content analysis on a total of 2,187 network analysis papers published in journals from 2003 to 2021. The results showed that the fields of Pedagogy, Interdisciplinary Research, Computer Science, Library and Information Science, Public Administration, and Business Administration were higher in terms of the number of research papers. From the perspective of journal, mega-journals were indicated as the most productive journals. However, when looking at the impact based on the number of citations, the strength of Public Administration, Library and Information Science, and Pedagogy is clearly revealed. The results of the analysis by authors can also confirm the higher impact of Journalism, Public Administration Science, and Library and Information Science. Of the 1,537 authors identified, very few authors are active in research, confirming the need to expand the researcher base. The results of content analysis showed that the weighted and non-directional network was the most common network type with using the research papers as a data set. Generally nodes are expressed as words and links are expressed as relationship. For network analysis, the use of KrKwic, UCINET, NetMiner, and NetDraw is the most prominent.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.95-105
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• 2018

This study empirically test the roles of network closure and structural hole on radical innovation in technological knowledge exchange network in Gumi cluster. In doing so, we build 2,550 firm network, transforming association*firm(2-mode) to firm*firm(1-mode) network data. In addition, in order to investigate firms' attributes, we conduct survey for 101 firms in Gumi cluster using random sampling, and finally collect 86 firm samples. For analysis, we use ridge regression since network density and efficiency, indices of network closure and structural hole respectively, has a high level of multicollinearity. The findings show that structural hole has a significant and positive impact on radical innovation, but network closure has a significant and negative impact on radical innovation. This study contributes to present an empirical evidence of debate on network closure and structural hole based on past conceptual discussions and literature review and further goes a long way towards strategy formulation to establish social capital in accomplishing radical innovation. Further research is required that pays closer attention to features of technological knowledge, innovation types and interaction between network closure and structural hole, directing efforts to structural characteristics of various networks.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.4
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• pp.19-41
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• 2007

This research has a goal which is suggesting the way of constructing 'Cluster' which mean scheming the commencement of an enterprise in an early stage. Now it is reorganized into a IT industry structure 'Time-to market growth' is burst as a big issue. in that point, this research analyze the core success factor which is drawing from the existing IT industrial complex, and then it will be used to draw up to the 'Idealistic growth-support Cluster' on the basis of it, we pulled out various issues about the Corporate in the early stage of its growth. Therefore, this research is focused on presenting the ideal network(net) by considering the Network that organizations and business in Cluster or the network including the factors linked organizations and business in Cluster. therefore, this research carried out three big analysis. from the case investigation we pulled out the core growth factor, and then we approached the analysis of net structure for making application to Network Analysis. and then we analyzed that the characteristics of the Network after measuring by on the basis of analyzing core growth factor. and especailly, this research carried out the Core analysis for recognition of Core- support-frame by base Centrality Test on the net which is composed of growth support organizations at each Business. Judging from this, we can help to make full use of resources for the network analysis in Cluster and establish the Network Strategy by Structure comparison between the structure of industry-Cluster and ideal Business-support networks on the basis of the analysis from the Core-success-factor