  Lexical semantic change (detecting shifts in the meaning and usage of words)
is an important task for social and cultural studies as well as for Natural
Language Processing applications. Diachronic word embeddings (time-sensitive
vector representations of words that preserve their meaning) have become the
standard resource for this task. However, given the significant computational
resources needed for their generation, very few resources exist that make
diachronic word embeddings available to the scientific community.
  In this paper we present DUKweb, a set of large-scale resources designed for
the diachronic analysis of contemporary English. DUKweb was created from the
JISC UK Web Domain Dataset (1996-2013), a very large archive which collects
resources from the Internet Archive that were hosted on domains ending in
`.uk'. DUKweb consists of a series word co-occurrence matrices and two types of
word embeddings for each year in the JISC UK Web Domain dataset. We show the
reuse potential of DUKweb and its quality standards via a case study on word
meaning change detection.
