REVIEW 1 cited by
Sentence Length
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
The distribution of sentence length in ordinary language is not well captured by the existing models. Here we survey previous models of sentence length and present our random walk model that offers both a better fit with the data and a better understanding of the distribution. We develop a generalization of KL divergence, discuss measuring the noise inherent in a corpus, and present a hyperparameter-free Bayesian model comparison method that has strong conceptual ties to Minimal Description Length modeling. The models we obtain require only a few dozen bits, orders of magnitude less than the naive nonparametric MDL models would.
Forward citations
Cited by 1 Pith paper
-
Fluctuations in email size modeled using a gamma-like distribution
A gamma-like email-size distribution fits the observed 2015 data better than the previous log-normal-like model, but the gain is small, fitted on the same data, and not statistically confirmed.
Discussion (0). Continue with ORCID to comment.