ArticleScientific reports2023
Temporal-topological properties of higher-order evolving networks.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- Persistent cycles and network resilience: a hypernetwork-based framework for temporal graph analysis.Scientific reports · 2026Article
- Temporal network analysis in systems biology: concepts, inference, and validation.Frontiers in bioinformatics · 2026Review
- Higher-order temporal network prediction and interpretation.PloS one · 2025Article
- The temporal dynamics of group interactions in higher-order social networks.Nature communications · 2024Article
- Higher-order correlations reveal complex memory in temporal hypergraphs.Nature communications · 2024Article
- Legal hypergraphs.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2024Article
- Patterns in Temporal Networks with Higher-Order Egocentric Structures.Entropy (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Human social interactions are typically recorded as time-specific dyadic interactions, and represented as evolving (temporal) networks, where links are activated/deactivated over time. However, individuals can interact in groups of more than two people. Such group interactions can be represented as higher-order events of an evolving network. Here, we propose methods to characterize the temporal-topological properties of higher-order events to compare networks and identify their (dis)similarities. We analyzed 8 real-world physical contact networks, finding the following: (a) Events of different orders close in time tend to be also close in topology; (b) Nodes participating in many different groups (events) of a given order tend to involve in many different groups (events) of another order; Thus, individuals tend to be consistently active or inactive in events across orders; (c) Local events that are close in topology are correlated in time, supporting observation (a). Differently, in 5 collaboration networks, observation (a) is almost absent; Consistently, no evident temporal correlation of local events has been observed in collaboration networks. Such differences between the two classes of networks may be explained by the fact that physical contacts are proximity based, in contrast to collaboration networks. Our methods may facilitate the investigation of how properties of higher-order events affect dynamic processes unfolding on them and possibly inspire the development of more refined models of higher-order time-varying 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.