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This is a Quantitative Study study.

Beyond Pairwise Network Interactions: Implications for Information Centrality

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This research demonstrates how hypergraph models enhance centrality measures in various settings, improving information flow and targeting.

Hypergraph-based centrality better explains project success, offering insights beyond traditional pairwise methods.
Evaluations in open-source software, high school interactions, and financial contexts reveal significant advantages over standard metrics.
Utilizing a two-step diffusion process for information modeling allows for more effective resource allocation in collaborative environments.
The approach supports better decision-making and improved allocation of attention in public health and market surveillance.

Lera et al. (2025) studied this question.

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This research demonstrates how hypergraph models enhance centrality measures in various settings, improving information flow and targeting.