• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.519-526
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• 2012

Human-human interaction network derived from Roman-fleuve, Togi was constructed. The network has a scale free properties as if most social networks do. The Togi is excellent model system for analyzing network dynamics because it has various characters and complex their interactions. The novel is composed of well-separated 5 sections. I constructed 5 different sub-netwotks from each section. As employing k-core algorithm as a useful tool for obtaining a core network from the complex networks, it is possible to obtain hidden and valuable information from a complex network. As gradually extending one section to another one, I constructed 4 different extended networks. The final one is whole network from the Togi. These results provide new insight that is analyzed by network-based approaches for network dynamics from literature, Togi.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.364-371
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• 2009

We analyzed romance of the three kingdoms written by Luo Guanzhong by using complex network to compare its properties with those of social network. The three kingdom network has a scale free and hierarchical network properties. Human-human interaction networks are dramatically changing in response to time and space. Due to lack of the dynamic interacting data, the researches only focus to analysis for properties of the statical networks. The romance of the three kingdoms is a Chinese historical novel based upon events from the end of the Han Dynasty, the Three Kingdoms era of China, and the reunification of the land. There are over a thousand characters, over a three thousand human-human interactions, and the dynamic changed in human-human interactions in the historical novel. Here, we introduce that a possible method for analyzing about dynamic changing of the complex network.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.427-435
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• 2010

We extracted core terms by constructing scientific item networks from textbooks, analyzing their structures, and investigating the connected information and their relationships. For this research, we chose three high-school textbooks from different publishers for each three subjects, i.e, Science, Biology I and Biology II, to construct networks by linking scientific items in each sentence, where used items were regarded as nodes. Scientific item networks from all textbooks showed scare-free character. When core networks were established by applying k-core algorithm which is one of generally used methods for removing lesser weighted nodes and links from complex network, they showed the modular structure. Science textbooks formed four main modules of physics, chemistry, biology and earth science, while Biology I and Biology II textbooks revealed core networks composed of more detailed specific items in each field. These findings demonstrate the structural characteristics of networks in textbooks, and suggest core scientific items helpful for students' understanding of concept in Science and Biology.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.5
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• pp.209-216
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• 2013

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes in terms of message delivery. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In this paper, we define a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also define a new measure, called the expended ego betweenness centrality. Through the intensive experiment with Barab$\acute{a}$si-Albert network model to generate the scale-free networks which most social networks have as their embedded feature, we also show that the nodes' importance rank based on the expanded ego betweenness centrality has high similarity with that based on the traditional betweenness centrality.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.1-13
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• 2007

In this research, we found out that bridging nodes have great effect on the robustness of protein-protein interaction networks. Until now, many researchers have focused on node's degree as node's essentiality. Hub nodes in the scale-free network are very essential in the network robustness. Some researchers have tried to relate node's essentiality with node's betweenness centrality. These approaches with betweenness centrality are reasonable but there is a positive relation between node's degree and betweenness centrality value. So, there are no differences between two approaches. We first define a bridging node as the node with low connectivity and high betweenness value, we then verify that such a bridging node is a primary factor in the network robustness. For a biological network database from Internet, we demonstrate that the removal of bridging nodes defragment an entire network severally and the importance of the bridging nodes in the network robustness.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1266-1275
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• 2004

Bioinformatics is concerned with the creation and development of advanced information and computational technologies for problems in biology. It is divided into genomics, proteomics and metabolimics. In metabolimics, an organism is represented by metabolic pathway, i.e., well-displayed graph, and so the graph drawing tool to draw pathway well is necessary to understand it comprehensively. In this paper, we design an improved drawing algorithm. It enhances the readability by making use of the bipartite graph. Also it is possible to draw large graph properly by considering the facts that metabolic pathway graph is scale-free network and is composed of circular components, hierarchic components and linear components.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.529-537
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• 2014

To establish a foundation to objectively interpret Chosun history, we construct people network of the Chosun dynasty. The network shows scale free network properties as if most social networks do. The people network is composed of 1,379 nodes and 3,874 links and its diameter is 14. To analysis of the network dynamics, whole network that is composed of 27 king networks were constructed by adding the first king, Taejo network to the second king, Jeongjong network and then continuously adding the next king networks. Interestingly, betweenness and closeness centralities were gradually decreased but stress centrality was drastically increased. These results indicate that information flow is gradually slowing and hub node position is more centrally oriented as growing the network. To elucidate key persons from the network, k-core and MCODE algorithms that can extract core or module structures from whole network were employed. It is a possible to obtain new insight and hidden information by analyzing network dynamics. Due to lack of the dynamic interacting data, there is a limit for network dynamic research. In spite of using concise data, this research provides us a possibility that annals of the Chosun dynasty are very useful historical data for analyzing network dynamics.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.106-106
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• 2001

네트웍의 용량의 개념이 없는 미세한 교통혼잡 도구로서 Microscopic시뮬레이션 모형인 Paramics가 소개된다. 모형의 기본구조가 설명되고, 특히 응용사례로서 서울시 교통관리 시스템을 설치함에 있어서 대안의 평가에 따른 제반 결과의 척도를 이끌어 내는 절차가 소개되었고, 아울러 결과가 분석되어 제시되었다. 이는 미시적 교통 시뮬레이션을 위한 고성능의 소프트웨어로서 각 차량들은 상세한 속성들을 가지고, ITS와 운전자와의 인터페이스를 모델링 할 뿐만 아니라 정확한 교통류, 대중교통 시간, 혼잡정보를 시뮬레이션 할 수 있는 장점이 있는바 적용 분야로서 여기까지가 있으나 혼잡이 있는 도로 네트워크 및 일반도로 네트워크와 ITS 인프라의 존재상황에서 제반 모델링이 가능한바 이를 통한 도시고속도로 관리시스템의 효과를 분석하였다. 신호의 영향, 첨단신호제어, 램프 미터링, 루프 검지기, 다양한 속도 표지, VMS 정보전략 등의 기능을 소개하고 금번 서울시의 사례를 통한 모형의 장단점을 보고한다. 아울러 이 시뮬레이션 모형의 한계도 함께 지적되었다.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.429-437
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• 2011

Movie network as a social network shows power-law distribution that is one of distinct properties in scale-free network. We constructed movie network from 799 Korea movies that screened from 2000 to 2009 and analyzed structural properties of the network. The 799 movies was classified three groups as a spectator mobilizing power. One million spectators mobilizing power movie was denoted the first class. The best 10 movie directors who produced at least three movies for ten years and had 70% the first class movie of them were selected. We also preferred the best 20 movie actors who played at least five movies for ten years and had 70% the first class movie of them. We re-constructed core movie network that composed the best 10 directors, the best 20 movie stars, and 157 movies that were produced by the directors or were played by the movie stars. We predict a possible combination of the director and movie actor as a category of the movie that has highly spectator mobilizing power. Here, we provide insight and method for producing high spectators mobilizing power movies

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.396-407
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• 2013

The role of influentials to maximize word-of-mouth effect can be seen to be very important. In this paper, we have the perspective of corporate marketing to understand Twitter influentials. We start from the point of view of who can induce eventually most exposure of tweets when he tweets the company's specific marketing messages. From this perspective, we observe both the follower influentials who have many followers and the retweet influentials who induce many retweets by visualizing graphs from network data collected via Twitter Search API. Although some users have small followers they may bring much more exposure than follower influentials if they can induce retweets by follower influentials. On the contrary, some retweet influentials who don't induce retweets by follower influentials may bring very little exposure. This suggests the fact that some small users who can induce retweets by influentials might have more important role than influentials themselves in order to increase the exposure of tweets. These users also are seen to have high centrality measures in the network structure.