A Comparison Study on the Weighted Network Centrality Measures of tnet and WNET

이재윤,

doi:10.3743/kosim.2013.30.4.241

Cited by 14 publications

(5 citation statements)

References 23 publications

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“…We used social network analysis (SNA) to calculate these measures. The form of the analysis is usually either an array of the social networks or a structure classified by different social network characteristics [ 48 ]. A variety of social network analysis methods exist to quantify network structures, such as centrality, density, structural holes, concentration, and modularity.…”

Section: Methodsmentioning

confidence: 99%

Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?

Hong

Sung

2021

IJERPH

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COVID-19 has sparked a debate on the vulnerability of densely populated cities. Some studies argue that high-density urban centers are more vulnerable to infectious diseases due to a higher chance of infection in crowded urban environments. Other studies, however, argue that connectivity rather than population density plays a more significant role in the spread of COVID-19. While several studies have examined the role of urban density and connectivity in Europe and the U.S., few studies have been conducted in Asian countries. This study aims to investigate the role of urban spatial structure on COVID-19 by comparing different measures of urban density and connectivity during the first eight months of the outbreak in Korea. Two measures of density were derived from the Korean census, and four measures of connectivity were computed using social network analysis of the Origin-Destination data from the 2020 Korea Transport Database. We fitted both OLS and negative binomial models to the number of confirmed COVID-19 patients and its infection rates at the county level, collected individually from regional government websites in Korea. Results show that both density and connectivity play an important role in the proliferation of the COVID-19 outbreak in Korea. However, we found that the connectivity measure, particularly a measure of network centrality, was a better indicator of COVID-19 proliferation than the density measures. Our findings imply that policies that take into account different types of connectivity between cities might be necessary to contain the outbreak in the early phase.

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Section: Methodsmentioning

confidence: 99%

Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?

Hong

Sung

2021

IJERPH

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“…Lee [41] first proposed the weighted triangle betweenness centrality, C TBi , in 2013, which is applied to evaluate the ability of a node as a mediator in the weighted network by computing the number of times the node plays the intermediary role between other nodes. For node v i , C TBi is expressed as:…”

Section: Weighted Triangle Betweenness Centralitymentioning

confidence: 99%

Long-Term Network Structure Evolution Investigation for Sustainability Improvement: An Empirical Analysis on Global Top Full-Service Carriers

Yang,

Jiang,

Chi

et al. 2024

Aerospace

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The continuous and strategic planning of full-service carriers plays a prominent role in transferring and adapting them into resilient full-service carrier network structures. The exploration of full-service carrier network structures using the latest long-term empirical data facilitates enhancing cognitive capabilities in aspects of identifying network development tendencies, readjusting network structures, and supporting determinations of strategic business routes. Aiming at providing sustainable transport network solutions with historical long-term network structure analysis, this paper researches the global top 10 full-service carriers’ air transport networks from 2007 to 2022, applied using social network analysis (SNA). The static metrics from local to path-based perspectives are adopted to explore the global network evolution trend, along with competitiveness characteristics over critical airports. The cascading failure model is applied as a key indicator to analyze the dynamic robustness capability for the network. The similarity changing feature among the selected networks over the past years from 2007 to 2022 is measured using the autocorrelation function (ACF). The results indicate that, from 2011 to 2019, the majority of full-service carrier networks belong to the network types of closed, structural symmetry and two-way transitivity. The critical airports in North America present superiority in terms of network efficiency over those in Europe, Asia, and Oceania. The 10 full-service carriers’ air transport networks all show the trend of being more destruction-resistant. During the COVID-19 pandemic period, the merger with other airlines and the signing of a joint venture agreement led to higher temporal variability in the network structure.

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“…( Evaluate, 2020 , Gong et al, 2018 , IATA, 2020 , Jo et al, 2014 , Kim et al, 2019 , Lee, 2013 , Matsumoto, 2007 , Ministry of Land, Infrastructure and Transport, 2017 , Park et al, 2016 )…”

Section: Uncited Referencesmentioning

confidence: 99%

Analysis of weighted network centrality for cold chain commodities in international air cargo under the COVID-19 pandemic

Park

Ahn

Son

2023

The Asian Journal of Shipping and Logistics

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A Comparison Study on the Weighted Network Centrality Measures of tnet and WNET

Cited by 14 publications

References 23 publications

Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?

Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?

Long-Term Network Structure Evolution Investigation for Sustainability Improvement: An Empirical Analysis on Global Top Full-Service Carriers

Analysis of weighted network centrality for cold chain commodities in international air cargo under the COVID-19 pandemic

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