Year: 2009
Type: conference-paper
Abstract: This paper presents a new statistical method for detecting and tracking changes in word meaning, based on Latent Semantic Analysis. By comparing the density of semantic vector clusters this method allows researchers to make statistical inferences on questions such as whether the meaning of a word changed across time or if a phonetic cluster is associated with a specific meaning. Possible applications of this method are then illustrated in tracing the semantic change of 'dog', 'do', and 'deer' in early English and examining and comparing phonaesthemes.
Authors: Eyal Sagi, Stefan Kaufmann, Brady Clark
Institution: Northwestern University
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W2080404274