Underlying dimensions in conceptual change
Katholieke Universiteit Leuven (Belgium)
Distributional semantic methods offer a powerful tool for analysing changes in the textual representation of lexically identifiable topics: an automated analysis of the changing contexts in which words like ‘migrant’ or ‘democracy’ appear reveals shifts in the conceptual associations of these concepts. Such a distributional method can be greatly enhanced by doubling it up upon itself, i.e. by distributionally identifying the similarity among context words associated with the target items, and subsequently analysing the latter in terms of the emergent underlying dimensions. The goal of this project is to: 1) apply and refine state-of-the-art vector space modelling and other distributional semantic methods to diachronic datasets, with a focus on higher-order collocates; 2) document examples of semantic change and their distributional dimensions; 3) form a general hypothesis about the distributional dimensions of conceptual change; 4) recommend a best practice workflow for similar applications. The linguistic focus of the project will be decided depending on the candidate’s background.