Extended Analysis of the Semantic Shift in Diachronic Word Embeddings for Spanish Before and After COVID-19

Abstract

Words can shift their meaning across time. This article shows the results obtained by the exploratory analysis of the semantic shifting on Spanish vocabulary using Diachronic Word Embeddings. Diachronic data consists of a 2018 Spanish corpus, before the COVID-19 outbreak, and a second corpus with documents from 2021. This paper addresses the construction of the diachronic Spanish word embeddings model, as well as the results obtained by the analysis using a non-supervised distance vector technique. In addition to the results shown in [1], this extended article discusses additional topics with the most semantic shift between those periods, like video games, cryptocurrencies, COVID-19 testing, COVID-19 vaccines, sanitizers, sports (soccer, basketball, cycling, tennis), pornography and K-Pop, in addition to COVID-19, masks, and vaccines treated in the first article.