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        <title>A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications</title>
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    <name type="personal">
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    <abstract>Historical linguists have identified multiple forms of lexical semantic change. We present a three-dimensional framework for integrating these forms and a unified computational methodology for evaluating them concurrently. The dimensions represent increases or decreases in semantic 1) sentiment (valence of a target word’s collocates), 2) intensity (emotional arousal of collocates or the frequency of intensifiers), and 3) breadth (diversity of contexts in which the target word appears). These dimensions can be complemented by evaluation of shifts in the frequency of the target words and the thematic content of its collocates. This framework enables lexical semantic change to be mapped economically and systematically and has applications in computational social science. We present an illustrative analysis of semantic shifts in mental health and mental illness in two corpora, demonstrating patterns of semantic change that illuminate contemporary concerns about pathologization, stigma, and concept creep.</abstract>
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%0 Conference Proceedings
%T A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications
%A Baes, Naomi
%A Haslam, Nick
%A Vylomova, Ekaterina
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F baes-etal-2024-multidimensional
%X Historical linguists have identified multiple forms of lexical semantic change. We present a three-dimensional framework for integrating these forms and a unified computational methodology for evaluating them concurrently. The dimensions represent increases or decreases in semantic 1) sentiment (valence of a target word’s collocates), 2) intensity (emotional arousal of collocates or the frequency of intensifiers), and 3) breadth (diversity of contexts in which the target word appears). These dimensions can be complemented by evaluation of shifts in the frequency of the target words and the thematic content of its collocates. This framework enables lexical semantic change to be mapped economically and systematically and has applications in computational social science. We present an illustrative analysis of semantic shifts in mental health and mental illness in two corpora, demonstrating patterns of semantic change that illuminate contemporary concerns about pathologization, stigma, and concept creep.
%U https://aclanthology.org/2024.acl-long.76
%P 1390-1415

Markdown (Informal)

[A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications](https://aclanthology.org/2024.acl-long.76) (Baes et al., ACL 2024)

• A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications (Baes et al., ACL 2024)

ACL

• Naomi Baes, Nick Haslam, and Ekaterina Vylomova. 2024. A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1390–1415, Bangkok, Thailand. Association for Computational Linguistics.