kehaosakest
kehaosakest is a metric used in computational linguistics and digital humanities to quantify the degree of semantic divergence between two corpora over a specified time period. The term was coined in the early 2020s by researchers at the Institute for Language Technology in Zurich as an extension of the well‑known KL‑divergence framework, with a particular focus on tracking the evolution of word senses in genre‑specific texts. The name combines the Greek root *kehou*, meaning “to divide,” with the suffix *sakest*, derived from an abbreviation of “semantic aspect cross‑entropy.”
Technically, a kehaosakest score is computed by first extracting frequency vectors of lemmas from two corpora,
Key applications include diachronic studies of literary styles, monitoring policy language in governmental documents, and assessing
Related concepts are semantic drift, lexical change detection, and the use of word embeddings to capture contextual