• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.95-104
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• 2018

Using network betweenness centrality we attempt to analyze the characteristics of Seoul metropolitan subway lines. Betweenness centrality highlights the importance of a node as a transfer point between any pairs of nodes. This 'transfer' characteristic is obviously of paramount importance in transit systems. For betweenness centrality, both traditional betweenness centrality measure and weighted betweenness centrality measure which uses monthly passenger flow amount between two stations are used. By comparing traditional and weighted betweenness centrality measures of lines characteristics of passenger flow can be identified. We also investigated factors which affect betweenness centrality. It is the number of passenger who get on or get off that significantly affects betweenness centrality measures. Through correlation analysis of the number of passenger and betweenness centrality, it is found out that Seoul metropolitan subway system is well designed in terms of regional distribution of population. Four measures are proposed which represent the passenger flow characteristics. It is shown they do not follow Power-law distribution, which means passenger flow is relatively evenly distributed among stations. It has been shown that the passenger flow characteristics of subway networks in other foreign cities such as Beijing, Boston and San Franciso do follow power-law distribution, that is, pretty much biased passenger flow traffic characteristics. In this study we have also tried to answer why passenger traffic flow of Seoul metropolitan subway network is more homogeneous compared to that of Beijing.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.127-146
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• 2013

The online social networking services (SNS) have been growing as the means of communication. In this study, we investigated word-of-mouth (WOM) effect under the SNS environment and evaluated the impact of message sender's influence on the WOM effect. Especially, this study focused on the betweenness centrality calculated through the social network analysis (SNA) of SNS network information, and proposed it as the measure of WOM message sender's influence, SNA may provide more accurate and objective measures than subjective self-reporting survey method. Fifty-one Facebook users responded to each of their four Facebook friends, who had been selected based on their betweenness centrality, Statistical analyses were performed using the responses and the betweenness centralities of the Facebook friends. The results showed that the direction (positive vs, negative) of a WOM message in SNS had an impact on the attitude of the message receiver toward the product. Moreover, the betweenness centrality of the message sender as well as his/her opinion leadership had a moderating effect on the WOM effect. Opinion leadership is a measure that has been frequently used for indicating the influence of WOM message sender in the previous studies. Considering the result that the betweenness centrality of the message sender was Significantly correlated to his/her opinion leadership, the betweenness centrality can be used for indicating the influence of WOM message sender.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.37-44
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• 2015

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes. 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 our past study, we defined 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 defined a new measure, called the expanded ego betweenness centrality. In this paper, We propose algorithm that quickly computes expanded ego betweenness centrality by exploiting structural properties of expanded ego network. Through the experiment with virtual network used Barab$\acute{a}$si-Albert network model to represent the generic social network and facebook network to represent actual social network, We show that the node's importance rank based on the expanded ego betweenness centrality has high similarity with that the node's importance rank based on the existing betweenness centrality. We also show that the proposed algorithm computes the expanded ego betweenness centrality quickly than existing algorithm.

• 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 Multimedia Information System
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• v.9 no.2
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• pp.121-126
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• 2022

The shortest path betweenness value of a node quantifies the amount of information passing through the node when all the pairs of nodes in the network exchange information in full capacity measured by the number of the shortest paths between the pairs assuming that the information travels in the shortest paths. It is calculated as the cumulative of the fractions of the number of shortest paths between the node pairs over how many of them actually pass through the node of interest. It's possible for a node to have zero or underrated betweenness value while sitting just next to the giant flow of information. These nodes may have a significant influence on the network when the normal flow of information is disrupted. We propose a betweenness centrality measure called collective betweenness that takes into account the surroundings of a node. We will compare our measure with other centrality metrics and show some applications of it.

• Journal of the Korean Society for Railway
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• v.20 no.3
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• pp.413-422
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• 2017

In this study we investigate the importance of the subway station using network centrality measures. For centrality measures, we have used betweenness centrality, closeness centrality, and degree centrality. A new measure called weighted betweenness centrality is proposed, that combines both traditional betweenness centrality and passenger flow between stations. Through correlation analysis and power-law analysis of passenger flow on the Seoul metropolitan subway network, we have shown that weighted betweenness centrality is a meaningful and practical measure. We have also shown that passenger flow between any two stations follows a highly skewed power-law distribution.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.105-115
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• 2020

This study examines the influence of the betweenness centrality on tertius gaudens orientation, relationship commitment, and individual learning performance within the university environment. The betweenness centrality explored the antecedent factor of tertius gaudens orientation. The relationship commitment explored the consequence factor of tertius gaudens orientation, and the learning performance explored the consequence factor of the relationship commitment. This survey was carried out by university students. Data were obtained from 74 respondents who have been studying tourism data analytics at one of the leading universities, in Seoul, Korea. In order to validate the research model, social network analysis tool, UCINET 6.689, and a structural equation modeling tool, SmartPLS 3.3.2, were used. The empirical result showed that all antecedent factors (betweenness centrality position, tertius gaudens orientation, and relationship commitment) of the learning performance were significant. In conclusion, this study discusses the research findings and implications. Then the limitations and future directions of the study were suggested.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.250-254
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• 2009

상수관망의 기능은 정수처리 된 양질의 물을 수용가에게 안전하게 공급하는 것이며, 이를 위해 상수관내에는 수용가에 충분한 양의 물을 공급할 수 있는 적정 유량과 압력이 유지되어야하고 최소기준치 이상의 잔류염소농도 유지 등의 적절한 수질을 만족시켜야한다. 하지만 상수관망은 상수관 파괴에 따른 오염물질 유입이나 테러와 같은 인위적인 오염물 주입 등의 갑작스런 사고에 의한 수질오염에 언제나 노출되어 있다. 이러한 수질오염사고 발생 시 신속한 대처를 위해서는 상수관망의 모든 절점에 수질측정 센서를 설치하는 것이 바람직하겠지만, 이는 경제적 측면과 센서의 유지 관리측면에서는 이상적이지 않다. 또한 발생 가능한 모든 상황에 대한 시뮬레이션 기반의 수질모델링을 통하여 적절한 수질오염 측정지점을 선정할 수도 있겠지만, 이는 상당한 시간과 계산능력을 요한다. 따라서 본 연구에서는 네트워크 분석기법 (Network Analysis)인 Betweenness Centrality와 수리해석 모형인 EPANET을 이용하여 상수관망의 수질오염측정지점 선정기법을 제안하였다. Betweenness Centrality는 네트워크를 구성하는 한 절점과 다른 한 절점을 연결시키는 특정 절점의 매개정도로 중심성을 측정하는 기법이다. Betweenness Centrality는 상수관망의 특정절점에 수질오염 사고가 발생하였을 때 오염원의 이동 가능한 경로의 수에 따라 그 값이 달라지며, 결과값에 의하여 수질오염측정지점이 선정된다. 본 연구에 의한 결과는 상수관망이 복잡하여 시뮬레이션을 통한 분석이 어렵고 많은 시간과 계산능력이 요구 될 경우 대안기법으로 활용될 수 있을 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.401-409
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• 2011

From a social network of n nodes connected by l lines, one may produce centrality measures such as closeness, betweenness and so on. In the past, the magnitude of n was around 1,000 or 10,000 at most. Nowadays, some networks have 10,000, 100,000 or even more than that. Thus, the scalability issue needs the attention of researchers. In this short paper, we explore random networks of the size around n = 100,000 by Monte-Carlo method and propose Monte-Carlo algorithms of computing closeness and betweenness centrality measures to study the small world properties of social networks.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.65-71
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• 2016

In this paper, we propose a novel analysis method and its algorithms to perform the betweenness centrality measurements on a valued and directed workflow-supported social network. The conventional workflow-supported social network model is to represent the existences of task transferring relationships among their performers by using a binary social network. However, it is necessary to consider not only the existences of task transferring relationships but also their quantities and directions in order to obtain much more effective and sophisticated analysis results. In conclusion, this paper newly defines a concept of valued and directed workflow-supported social network, and its betweenness centrality analysis method and algorithms. Especially, to verify the proposed method and algorithms, we try to apply the conventional method and the proposed method to an example workflow model respectively, and compare their betweenness centrality analysis results.