ArticlePeerJ. Computer science2023
The critical node detection problem in hypergraphs using weighted node degree centrality.
Article in PeerJ. Computer science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- KSGR: An Influential Node Identification Algorithm for Directed Networks Integrating Reverse Reachability and Structural Enhancement Mechanisms.Entropy (Basel, Switzerland) · 2026Article
- Food addiction in children: a network analysis of nutritional, metabolic, and sociodemographic factors.Journal of eating disorders · 2025Article
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1 author.
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Abstract
Network analysis is an indispensable part of today's academic field. Among the different types of networks, the more complex hypergraphs can provide an excellent challenge and new angles for analysis. This study proposes a variant of the critical node detection problem for hypergraphs using weighted node degree centrality as a form of importance metric. An analysis is done on both generated synthetic networks and real-world derived data on the topic of United States House and Senate committees, using a newly designed algorithm. The numerical results show that the combination of the critical node detection on hypergraphs with the weighted node degree centrality provides promising results and the topic is worth exploring further.
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