Semantic micro-dynamics as a reflex of occurrence frequency: a semantic networks approach

Abstract: This article correlates fine-grained semantic variability and change with measures of occurrence frequency to investigate whether a word’s degree of semantic change is sensitive to how often it is used. We show that this sensitivity can be detected within a short time span (i.e., 20 years), basing our analysis on a large corpus of German allowing for a high temporal resolution (i.e., per month). We measure semantic variability and change with the help of local semantic networks, combining elements of deep learning methodology and graph theory. Our micro-scale analysis complements previous macro-scale studies from the field of natural language processing, corroborating the finding that high token frequency has a negative effect on the degree of semantic change in a lexical item. We relate this relationship to the role of exemplars for establishing form–function pairings between words and their habitual usage contexts.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Semantic micro-dynamics as a reflex of occurrence frequency: a semantic networks approach ; volume:34 ; number:3-4 ; year:2023 ; pages:533-568 ; extent:036 ; Cognitive linguistics ; 34, Heft 3-4 (2023), 533-568 (gesamt 036)

Beteiligte, Orts- und Zeitangaben

• Urheber: Baumann, Andreas ; Hofmann, Klaus ; Marakasova, Anna ; Neidhardt, Julia ; Wissik, Tanja

Weitere Informationen

• DOI: 10.1515/cog-2022-0008
• URN: urn:nbn:de:101:1-2023110813265666672083
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 14.08.2025, 10:45 MESZ