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

Here we test Neutral models against the evolution of English word frequencyand vocabulary at the population scale, as recorded in annual word frequenciesfrom three centuries of English language books. Against these data, we testboth static and dynamic predictions of two neutral models, including therelation between corpus size and vocabulary size, frequency distributions, andturnover within those frequency distributions. Although a commonly used Neutralmodel fails to replicate all these emergent properties at once, we find thatmodified two-stage Neutral model does replicate the static and dynamicproperties of the corpus data. This two-stage model is meant to represent arelatively small corpus (population) of English books, analogous to a `canon',sampled by an exponentially increasing corpus of books in the wider populationof authors. More broadly, this mode -- a smaller neutral model within a largerneutral model -- could represent more broadly those situations where massattention is focused on a small subset of the cultural variants.

Neutral evolution and turnover over centuries of English word popularity