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A computational analysis of crosslinguistic regularity in semantic change

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dc.contributor.author Fugikawa, Olivia
dc.contributor.author Hayman, Oliver
dc.contributor.author Liu, Raymond
dc.contributor.author Yu, Lei
dc.contributor.author Brochhagen, Thomas
dc.contributor.author Xu, Yang
dc.date.accessioned 2023-07-05T07:03:45Z
dc.date.available 2023-07-05T07:03:45Z
dc.date.issued 2023
dc.identifier.citation Fugikawa O, Hayman O, Liu R, Yu L, Brochhagen T, Xu Y. A computational analysis of crosslinguistic regularity in semantic change. Front. Commun. 2023;8:1136338. DOI: 10.3389/fcomm.2023.1136338
dc.identifier.issn 2297-900X
dc.identifier.uri http://hdl.handle.net/10230/57466
dc.description.abstract Semantic change is attested commonly in the historical development of lexicons across the world’s languages. Extensive research has sought to characterize regularity in semantic change, but existing studies have typically relied on manual approaches or the analysis of a restricted set of languages. We present a large-scale computational analysis to explore regular patterns in word meaning change shared across many languages. We focus on two levels of analysis: (1) regularity in directionality, which we explore by inferring the historical direction of semantic change between a sourcemeaning and a targetmeaning; (2) regularity in source-target mapping, which we explore by inferring the target meaning given a sourcemeaning.We work with DatSemShift, the world’s largest public database of semantic change that records thousands ofmeaning changes fromover hundreds of languages. For directionality inference, we find that concreteness explains directionality in more than 70% of the attested cases of semantic change and is the strongest predictor among the alternatives including frequency and valence. For target inference, we find that a parallelogram-style analogy model based on contextual embeddings predicts the attested source-targetmappings substantially better than chance and similarity-based models. Clustering the meaning pairs of semantic change reveals regular meaning shiftings between domains, such as body parts to geological formations. Our study provides an automated approach and large-scale evidence for multifaceted regularity in semantic change across languages.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Frontiers
dc.relation.ispartof Frontiers in communication. 2023;8:1136338.
dc.rights © 2023 Fugikawa, Hayman, Liu, Yu, Brochhagen and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.title A computational analysis of crosslinguistic regularity in semantic change
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://dx.doi.org/10.3389/fcomm.2023.1136338
dc.subject.keyword Word meaning
dc.subject.keyword Historical semantics
dc.subject.keyword Semantic change
dc.subject.keyword Crosslinguistic regularity
dc.subject.keyword Computational analysis
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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