ArticlePloS one2022
A spatial interaction incorporated betweenness centrality measure.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Haul-Out Site Use and Connectivity of Harbour Seals Between Management Units in Southern Scandinavia.Ecology and evolution · 2026Article
- Analysing health misinformation with advanced centrality metrics in online social networks.PLOS digital health · 2025Article
- Seasonal Dynamics in Soil Properties Along a Roadway Corridor: A Network Analysis Approach.Materials (Basel, Switzerland) · 2025Article
- Crochet increases attention through a requiring motor skill learning.Scientific reports · 2025Article
- Cognitive Normal Older Adults with APOE-2 Allele Show a Distinctive Functional Connectivity Pattern in Response to Cerebral Aβ Deposition.International journal of molecular sciences · 2023Article
- Identification of genes associated with spontaneous regression of neuroblastoma.Pediatric discovery · 2023Article
- Article
- Navigating the asthma network on Twitter: Insights from social network and sentiment analysis.Digital healthArticle
- Exploring the link trend in the field of coronaviruses and cognitive impairment: A bibliometric analysis based on bibliometrix.Brain circulationArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Betweenness centrality (BC) is widely used to identify critical nodes in a network by exploring the ability of all nodes to act as intermediaries for information exchange. However, one of its assumptions, i.e., the contributions of all shortest paths are equal, is inconsistent with variations in spatial interactions along these paths and has been questioned when applied to spatial networks. Hence, this paper proposes a spatial interaction incorporated betweenness centrality (SIBC) for spatial networks. SIBC weights the shortest path between each node pair according to the intensity of spatial interaction between them, emphasizing the combination of a network structure and spatial interactions. To test the rationality and validity of SIBC in identifying critical nodes and edges, two specific forms of SIBC are applied to the Shenzhen street network and China's intercity network. The results demonstrate that SIBC is more significant than BC when we also focus on the network functionality rather than only on the network structure. Moreover, the good performance of SIBC in robustness analysis illustrates its application value in improving network efficiency. This study highlights the meaning of introducing spatial configuration into empirical models of complex networks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.