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Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings

Shoemark, Philippa and Liza, Farhana Ferdousi and Nguyen, Dong and Hale, Scott and McGillivray, Barbara (2020) Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019-11-03 - 2019-11-07, Hong Kong.

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Abstract

Word embeddings are increasingly used for the automatic detection of semantic change; yet, a robust evaluation and systematic comparison of the choices involved has been lacking. We propose a new evaluation framework for semantic change detection and find that (i) using the whole time series is preferable over only comparing between the first and last time points; (ii) independently trained and aligned embeddings perform better than continuously trained embeddings for long time periods; and (iii) that the reference point for comparison matters. We also present an analysis of the changes detected on a large Twitter dataset spanning 5.5 years.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 04 Dec 2020 20:04
Last Modified: 23 Sep 2022 19:38
URI: http://repository.essex.ac.uk/id/eprint/27161

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