Using context variation indexes for the detection of semantic neologisms

Abstract

Semantic neologism detection is a complex issue in the field. SNs do not instil a feeling of novelty like formal neologisms because they already exist in the language, their change is only at a semantic level. This difficulty is prevalent when automating the identification process. The literature on the topic defends that the term’s context is the best tool for detection, as the term changes meaning, so do the words it collocates with. This study presents a new method of automatic detection that uses context variation indexes calculated employing diachronic corpora. This approach is much simpler than other state-of-the-art procedures because it depends less on other computational tools and requires less software maintenance. The method is tested on 100 Spanish and Catalan terms. All tests demonstrated consistent performance. The results highlight the importance of term frequency and usage frequency of the neological sense as key factors for its success.