  In terminology work, natural language processing, and digital humanities,
several studies address the analysis of variations in context and meaning of
terms in order to detect semantic change and the evolution of terms. We
distinguish three different approaches to describe contextual variations:
methods based on the analysis of patterns and linguistic clues, methods
exploring the latent semantic space of single words, and methods for the
analysis of topic membership. The paper presents the notion of context
volatility as a new measure for detecting semantic change and applies it to key
term extraction in a political science case study. The measure quantifies the
dynamics of a term's contextual variation within a diachronic corpus to
identify periods of time that are characterised by intense controversial
debates or substantial semantic transformations.
