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Corpus Methods for Semantics: Quantitative studies in polysemy and synonymy
Edited by Dylan Glynn and Justyna A. Robinson
[Human Cognitive Processing 43] 2014
► pp. 87–115

Quantifying polysemy in Cognitive Sociolinguistics

ORCID logo | University of Sussex

This chapter uses various statistical techniques to explore the extralinguistic grounding of individual conceptualisations of polysemous adjectives in English, such as awesome, gay, wicked. It considers the extent to which individual conceptualisations are non-random and can be related to the socio-demographic characteristics of the speaker. The experimental survey data collected from 72 speakers is analysed via hierarchical agglomerative clustering, decision tree analysis, and logistic regression analysis. The results reveal that not only individual adjectives, as indicated in Robinson (2010a), but whole groups of polysemous adjectives currently undergoing semantic change form usage patterns that can be explained by a very similar sociolinguistic distribution. This study demonstrates that employing a socio-cognitive perspective when researching polysemy is hugely advantageous.

Keywords: adjectives, decision tree analyses, hierarchical agglomerative clustering, logistic regression, semantic change, semantic variation
Published online: 6 November 2014
DOI logo
https://doi.org/10.1075/hcp.43.04rob
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