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    Lexical Variation and Change

    A Distributional Semantic Approach

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    Author(s)
    Geeraerts, Dirk
    Speelman, Dirk
    Heylen, Kris
    Montes, Mariana
    De Pascale, Stefano
    Franco, Karlien
    Lang, Michael
    Language
    English
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    Abstract
    Distributional semantics embodies the idea that the context in which a word occurs reveals the meaning of that word. In contemporary corpus linguistics, that idea takes shape in various types of quantitative context analysis. This monograph explores how count-based token-level semantic vector spaces, as an advanced form of such a quantitative methodology, can be applied to the study of polysemy, lexical variation, and lectometry. What can distributional models reveal about meaning? How can they be used to analyse the semantic relationship between near-synonyms? And how can they contribute to the study of lexical variation as a sociolinguistic variable? The book details the conceptual background of lexical semantic and lexical variation research, explains the mechanism of distributional modelling, and introduces distributional workflows and corpus linguistic tools to answer the questions. Combining a cognitive linguistic interest in meaning with a sociolinguistic interest in variation, it illustrates that distributional methodology with case studies on Dutch and Spanish lexical data, focusing on the value of distributional models for semantic analysis, the interaction of semasiological and onomasiological change, and sociolinguistic issues of lexical standardization and pluricentricity.
    URI
    https://library.oapen.org/handle/20.500.12657/85665
    Keywords
    distributional semantics, lexical semantics, lexicology, lexical variation, corpus semantics, lectometry, cognitive linguistics
    DOI
    10.1093/oso/9780198890676.001.0001
    ISBN
    9780198890676
    Publisher
    Oxford University Press
    Publisher website
    https://global.oup.com/
    Publication date and place
    Oxford, 2024
    Grantor
    • KU Leuven
    Pages
    337
    Rights
    https://creativecommons.org/licenses/by-nc-nd/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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