  We perform an interdisciplinary large-scale evaluation for detecting lexical
semantic divergences in a diachronic and in a synchronic task: semantic sense
changes across time, and semantic sense changes across domains. Our work
addresses the superficialness and lack of comparison in assessing models of
diachronic lexical change, by bringing together and extending benchmark models
on a common state-of-the-art evaluation task. In addition, we demonstrate that
the same evaluation task and modelling approaches can successfully be utilised
for the synchronic detection of domain-specific sense divergences in the field
of term extraction.
