• Title/Summary/Keyword: Weighted Betweenness Centrality

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Network Betweenness Centrality and Passenger Flow Analysis of Seoul Metropolitan Subway Lines (서울 수도권 지하철망의 호선별 망 매개 중심성과 승객 흐름 분석)

  • Lee, Kang Won;Lee, Jung Won
    • 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.

Analysis of Seoul Metropolitan Subway Network Characteristics Using Network Centrality Measures (네트워크 중심성 지표를 이용한 서울 수도권 지하철망 특성 분석)

  • Lee, Jeong Won;Lee, Kang Won
    • 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.

A Comparison Study on the Weighted Network Centrality Measures of tnet and WNET (tnet과 WNET의 가중 네트워크 중심성 지수 비교 연구)

  • Lee, Jae Yun
    • Journal of the Korean Society for information Management
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    • v.30 no.4
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    • pp.241-264
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    • 2013
  • This study compared and analyzed weighted network centrality measures supported by Opsahl's tnet and Lee's WNET, which are free softwares for weighted network analysis. Three node centrality measures including weighted degree, weighted closeness, and weighted betweenness are supported by tnet, and four node centrality measures including nearest neighbor centrality, mean association, mean profile association, triangle betweenness centrality are supported by WNET. An experimental analysis carried out on artificial network data showed tnet's high sensitiveness on linear transformations of link weights, however, WNET's centrality measures were insensitive to linear transformations. Seven centrality measures from both tools, tnet and WNET, were calculated on six real network datasets. The results showed the characteristics of weighted network centrality measures of tnet and WNET, and the relationships between them were also discussed.

A Comparative Study on the Centrality Measures for Analyzing Research Collaboration Networks (공동연구 네트워크 분석을 위한 중심성 지수에 대한 비교 연구)

  • Lee, Jae Yun
    • Journal of the Korean Society for information Management
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    • v.31 no.3
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    • pp.153-179
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    • 2014
  • This study explores the characteristics of centrality measures for analyzing researchers' impact and structural positions in research collaboration networks. We investigate four binary network centrality measures (degree centrality, closeness centrality, betweenness centrality, and PageRank), and seven existing weighted network centrality measures (triangle betweenness centrality, mean association, weighted PageRank, collaboration h-index, collaboration hs-index, complex degree centrality, and c-index) for research collaboration networks. And we propose SSR, which is a new weighted centrality measure for collaboration networks. Using research collaboration data from three different research domains including architecture, library and information science, and marketing, the above twelve centrality measures are calculated and compared each other. Results indicate that the weighted network centrality measures are needed to consider collaboration strength as well as collaboration range in research collaboration networks. We also recommend that when considering both collaboration strength and range, it is appropriate to apply triangle betweenness centrality and SSR to investigate global centrality and local centrality in collaboration networks.

A Generalized Measure for Local Centralities in Weighted Networks (가중 네트워크를 위한 일반화된 지역중심성 지수)

  • Lee, Jae Yun
    • Journal of the Korean Society for information Management
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    • v.32 no.2
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    • pp.7-23
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    • 2015
  • While there are several measures for node centralities, such as betweenness and degree, few centrality measures for local centralities in weighted networks have been suggested. This study developed a generalized centrality measure for calculating local centralities in weighted networks. Neighbor centrality, which was suggested in this study, is the generalization of the degree centrality for binary networks and the nearest neighbor centrality for weighted networks with the parameter ${\alpha}$. The characteristics of suggested measure and the proper value of parameter ${\alpha}$ are investigated with 6 real network datasets and the results are reported.

Privacy Protection Method for Sensitive Weighted Edges in Social Networks

  • Gong, Weihua;Jin, Rong;Li, Yanjun;Yang, Lianghuai;Mei, Jianping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.540-557
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    • 2021
  • Privacy vulnerability of social networks is one of the major concerns for social science research and business analysis. Most existing studies which mainly focus on un-weighted network graph, have designed various privacy models similar to k-anonymity to prevent data disclosure of vertex attributes or relationships, but they may be suffered from serious problems of huge information loss and significant modification of key properties of the network structure. Furthermore, there still lacks further considerations of privacy protection for important sensitive edges in weighted social networks. To address this problem, this paper proposes a privacy preserving method to protect sensitive weighted edges. Firstly, the sensitive edges are differentiated from weighted edges according to the edge betweenness centrality, which evaluates the importance of entities in social network. Then, the perturbation operations are used to preserve the privacy of weighted social network by adding some pseudo-edges or modifying specific edge weights, so that the bottleneck problem of information flow can be well resolved in key area of the social network. Experimental results show that the proposed method can not only effectively preserve the sensitive edges with lower computation cost, but also maintain the stability of the network structures. Further, the capability of defending against malicious attacks to important sensitive edges has been greatly improved.

Arab Spring Effects on Meanings for Islamist Web Terms and on Web Hyperlink Networks among Muslim-Majority Nations: A Naturalistic Field Experiment

  • Danowski, James A.;Park, Han Woo
    • Journal of Contemporary Eastern Asia
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    • v.13 no.2
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    • pp.15-39
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    • 2014
  • This research conducted a before/after naturalistic field experiment, with the early Arab Spring as the treatment. Compared to before the early Arab Spring, after the observation period the associations became stronger among the Web terms: 'Jihad, Sharia, innovation, democracy and civil society.' The Western concept of civil society transformed into a central Islamist ideological component. At another level, the inter-nation network based on Jihad-weighted Web hyperlinks between pairs of 46 Muslim Majority (MM) nations found Iran in one of the top two positions of flow betweenness centrality, a measure of network power, both before and after early Arab Spring. In contrast, Somalia, UAE, Egypt, Libya, and Sudan increased most in network flow betweenness centrality. The MM 'Jihad'-centric word co-occurrence network more than tripled in size, and the semantic structure more became entropic. This media "cloud" perhaps billowed as Islamist groups changed their material-level relationships and the corresponding media representations of Jihad among them changed after early Arab Spring. Future research could investigate various rival explanations for this naturalistic field experiment's findings.

Analyzing the Network of Academic Disciplines with Journal Contributions of Korean Researchers (연구자의 투고 학술지 현황에 근거한 국내 학문분야 네트워크 분석)

  • Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.25 no.4
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    • pp.327-345
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    • 2008
  • The main purposes of this study are to construct a Korean science network from journal contributions data of Korean researchers, and to analyze the structure and characteristics of the network. First of all, the association matrix of 140 scholarly domains are calculated based on the number of contributions in common journals, and then the Pathfinder network algorithm is applied to those matrix. The resulting network has several hubs such as 'Biology', 'Korean Language & Linguistics', 'Physics', etc. The entropy formula and several centrality measures for the weighted networks are adopted to identify the centralities and interdisciplinarity of each scholarly domain. In particular, the date hubs, which have several weak links, are successively distinguished by local and global triangle betweenness centrality measures.

Assessing conservation priorities of unexecuted urban parks in Seoul using ecological network and accessibility analyses (생태네트워크와 접근성 분석에 의한 서울시 미집행 도시공원의 보전 우선순위 평가)

  • Kang, Wan-Mo;Song, Young-Keun;Sung, Hyun-Chan;Lee, Dong-Kun
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.21 no.2
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    • pp.53-64
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    • 2018
  • This study aims to quantitatively evaluate the conservation priorities of unexecuted urban parks in Seoul both from an ecological and public perspective. To this end, two methodologies, ecological network analysis based on graph and circuit theory and accessibility analysis, were employed in order to assess ecological connectivity of and public accessibility to unexecuted parks, respectively. This study applied linkage-mapping methods (shortest path and current flow betweenness centrality) of connectivity analysis to an integrated map of landscape permeability. The population-weighted accessibility to unexecuted parks was measured based on a negative exponential distance decay function. As a result, for both ecological connectivity and accessibility, Gwanaksan, Suraksan, and Bulamsan urban natural parks are found to be the most important (rank 1-3) to be conserved. For these sites, inner park areas with conservation priorities for connectivity and accessibility were identified. The findings of the study can be used for giving conservation priority to the unexecuted urban parks in terms of long-term sustainable urban planning.

Are there network differences between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura?

  • Junseok Jang;Sungyeong Ryu;Dong Ah Lee;Kang Min Park
    • Annals of Clinical Neurophysiology
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    • v.25 no.2
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    • pp.93-102
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    • 2023
  • Background: We aimed to identify any differences in the structural covariance network based on structural volume and those in the functional network based on cerebral blood flow between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura. Methods: We prospectively enrolled 27 patients with migraine without aura, all of whom had unilateral migraine pain. We defined the ipsilateral hemisphere as the side of migraine pain. We measured structural volumes on three-dimensional T1-weighted images and cerebral blood flow using arterial spin labeling magnetic resonance imaging. We then analyzed the structural covariance network based on structural volume and the functional network based on cerebral blood flow using graph theory. Results: There were no significant differences in structural volume or cerebral blood flow between the ipsilateral and contralateral hemispheres. However, there were significant differences between the hemispheres in the structural covariance network and the functional network. In the structural covariance network, the betweenness centrality of the thalamus was lower in the ipsilateral hemisphere than in the contralateral hemisphere. In the functional network, the betweenness centrality of the anterior cingulate and paracingulate gyrus was lower in the ipsilateral hemisphere than in the contralateral hemisphere, while that of the opercular part of the inferior frontal gyrus was higher in the former hemisphere. Conclusions: The present findings indicate that there are significant differences in the structural covariance network and the functional network between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura.