UNIMIB @ DIACR-Ita: Aligning Distributional Embeddings with a Compass for Semantic Change Detection in the Italian Language
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11 mai 2021
- doi: 10.4000/books.aaccademia.7688
- eisbn: 9791280136329
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
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EVALITA COVID-19 Infodemic linguistica computazionale Automatic Misogyny Identification Misogyny on Twitter Posts AlBERTo Convolutional Neural Network BERT Model Hate Speech Detection Multimodal Meme Detection MEME management Language Game ``La Ghigliottina'' Language & Linguistics LAN000000 CBXSujets proches
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Federico Belotti et al., « UNIMIB @ DIACR-Ita: Aligning Distributional Embeddings with a Compass for Semantic Change Detection in the Italian Language », Accademia University Press, ID : 10.4000/books.aaccademia.7688
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Résumé
In this paper, we present our results related to the EVALITA 2020 challenge, DIACR-Ita, for semantic change detection for the Italian language. Our approach is based on measuring the semantic distance across time-specific word vectors generated with Compass-aligned Distributional Embeddings (CADE). We first generate temporal embeddings with CADE, a strategy to align word embeddings that are specific for each time period; the quality of this alignment is the main asset of our proposal. We then measure the semantic shift of each word, combining two different semantic shift measures. Eventually, we classify a word meaning as changed or not changed by defining a threshold over the semantic distance across time.