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.
REF use a variation of Latent Semantic Analysis to identify semantic change of specific words from early to modern English.
Semantic Density Analysis: Comparing Word Meaning across Time and Phonetic Space
Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
Computer Science