New Metrics for Node Importance Evaluation in Occupational Injury Network
Complex networks provide a convenient way to model the process of occupational injury occurrence at the system level, and node importance metrics are usually employed to quantify the influence of the factors leading to injuries. However, the traditional metrics such as degree and betweenness are bas...
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doaj-061d651325a74bbd9df3a2cb6dfc2e172021-03-29T22:56:42ZengIEEEIEEE Access2169-35362019-01-017618746188210.1109/ACCESS.2019.29161728712450New Metrics for Node Importance Evaluation in Occupational Injury NetworkXinbo Ai0https://orcid.org/0000-0003-2711-6313Automation School, Beijing University of Posts and Telecommunications, Beijing, ChinaComplex networks provide a convenient way to model the process of occupational injury occurrence at the system level, and node importance metrics are usually employed to quantify the influence of the factors leading to injuries. However, the traditional metrics such as degree and betweenness are based on the supposition that the network is a homogeneous one and the types of its nodes have to be the same. To describe the injury occurrence, there should be at least two types of nodes, i.e., source nodes and injury nodes. Since this network is heterogeneous in nature, traditional metrics for node importance evaluation are no longer applicable. Hence, we propose two metrics: radial degree and partial betweenness, to quantify the contribution of the source nodes. The former is to describe their induction capabilities, while the latter to depict their control capabilities. The composite score of these two metrics is utilized to evaluate the node importance. The empirical analysis on a total of 438 fatal accident reports in Beijing from 2004 to 2018 showed that our method notably outperformed several state-of-art metrics in evaluating and identifying the crucial nodes.https://ieeexplore.ieee.org/document/8712450/Occupational injurycomplex networksheterogeneous networknode importance |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xinbo Ai |
spellingShingle |
Xinbo Ai New Metrics for Node Importance Evaluation in Occupational Injury Network IEEE Access Occupational injury complex networks heterogeneous network node importance |
author_facet |
Xinbo Ai |
author_sort |
Xinbo Ai |
title |
New Metrics for Node Importance Evaluation in Occupational Injury Network |
title_short |
New Metrics for Node Importance Evaluation in Occupational Injury Network |
title_full |
New Metrics for Node Importance Evaluation in Occupational Injury Network |
title_fullStr |
New Metrics for Node Importance Evaluation in Occupational Injury Network |
title_full_unstemmed |
New Metrics for Node Importance Evaluation in Occupational Injury Network |
title_sort |
new metrics for node importance evaluation in occupational injury network |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
Complex networks provide a convenient way to model the process of occupational injury occurrence at the system level, and node importance metrics are usually employed to quantify the influence of the factors leading to injuries. However, the traditional metrics such as degree and betweenness are based on the supposition that the network is a homogeneous one and the types of its nodes have to be the same. To describe the injury occurrence, there should be at least two types of nodes, i.e., source nodes and injury nodes. Since this network is heterogeneous in nature, traditional metrics for node importance evaluation are no longer applicable. Hence, we propose two metrics: radial degree and partial betweenness, to quantify the contribution of the source nodes. The former is to describe their induction capabilities, while the latter to depict their control capabilities. The composite score of these two metrics is utilized to evaluate the node importance. The empirical analysis on a total of 438 fatal accident reports in Beijing from 2004 to 2018 showed that our method notably outperformed several state-of-art metrics in evaluating and identifying the crucial nodes. |
topic |
Occupational injury complex networks heterogeneous network node importance |
url |
https://ieeexplore.ieee.org/document/8712450/ |
work_keys_str_mv |
AT xinboai newmetricsfornodeimportanceevaluationinoccupationalinjurynetwork |
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1724190396709339136 |