ArticlePhysical review letters2016
Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation.
Article in Physical review letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Introduction to correlation networks: Interdisciplinary approaches beyond thresholding.Physics reports · 2025Article
- Time-resolved connectivity reveals the "how" and "when" of brain networks reconfiguration during face processing.Neuroimage. Reports · 2021Article
- Symmetries and cluster synchronization in multilayer networks.Nature communications · 2020Article
- Community detection in networks without observing edges.Science advances · 2020Article
- Application of hyperbolic geometry in link prediction of multiplex networks.Scientific reports · 2019Article
- Transient crosslinking kinetics optimize gene cluster interactions.PLoS computational biology · 2019Article
- NETWORK-ENSEMBLE COMPARISONS WITH STOCHASTIC REWIRING AND VON NEUMANN ENTROPY.SIAM journal on applied mathematics · 2018Article
- Article
- EIGENVECTOR-BASED CENTRALITY MEASURES FOR TEMPORAL NETWORKSMultiscale modeling & simulation : a SIAM interdisciplinary journal · 2017Article
- Clustering network layers with the strata multilayer stochastic block model.IEEE transactions on network science and engineeringArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common-but not well understood-practice of thresholding pairwise-interaction data to obtain sparse network representations.
Identifiers
What OpenQuestion holds
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.