English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Some authors have recently argued that a finite-size scaling law for thetext-length dependence of word-frequency distributions cannot be conceptuallyvalid. Here we give solid quantitative evidence for the validity of suchscaling law, both using careful statistical tests and analytical argumentsbased on the generalized central-limit theorem applied to the moments of thedistribution (and obtaining a novel derivation of Heaps' law as a by-product).We also find that the picture of word-frequency distributions with power-lawexponents that decrease with text length [Yan and Minnhagen, Physica A 444, 828(2016)] does not stand with rigorous statistical analysis. Instead, we showthat the distributions are perfectly described by power-law tails with stableexponents, whose values are close to 2, in agreement with the classical Zipf'slaw. Some misconceptions about scaling are also clarified.

Dependence of exponents on text length versus finite-size scaling for word-frequency distributions