Introduces a nonparametric inference procedure based on a sparse signed graphon model that yields valid confidence intervals for balance parameters and reports strong empirical evidence for balance theory across real signed networks.
Bootstrapping networks with latent space structure
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
stat.ME 2years
2024 2verdicts
UNVERDICTED 2representative citing papers
Proves node subsampling asymptotically approximates joint distribution of network moments under sparse graphon, enabling two-sample tests for unmatchable networks with unequal densities.
citing papers explorer
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Nonparametric Inference for Balance in Signed Networks
Introduces a nonparametric inference procedure based on a sparse signed graphon model that yields valid confidence intervals for balance parameters and reports strong empirical evidence for balance theory across real signed networks.
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Multivariate Inference of Network Moments by Subsampling
Proves node subsampling asymptotically approximates joint distribution of network moments under sparse graphon, enabling two-sample tests for unmatchable networks with unequal densities.