@inproceedings{horn-2021-exploring,
title = "Exploring Word Usage Change with Continuously Evolving Embeddings",
author = "Horn, Franziska",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-demo.35",
doi = "10.18653/v1/2021.acl-demo.35",
pages = "290--297",
abstract = "The usage of individual words can change over time, for example, when words experience a semantic shift. As text datasets generally comprise documents that were collected over a longer period of time, examining word usage changes in a corpus can often reveal interesting patterns. In this paper, we introduce a simple and intuitive way to track word usage changes via continuously evolving embeddings, computed as a weighted running average of transformer-based contextualized embeddings. We demonstrate our approach on a corpus of recent New York Times article snippets and provide code for an easy to use web app to conveniently explore semantic shifts with interactive plots.",
}
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%0 Conference Proceedings
%T Exploring Word Usage Change with Continuously Evolving Embeddings
%A Horn, Franziska
%S Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F horn-2021-exploring
%X The usage of individual words can change over time, for example, when words experience a semantic shift. As text datasets generally comprise documents that were collected over a longer period of time, examining word usage changes in a corpus can often reveal interesting patterns. In this paper, we introduce a simple and intuitive way to track word usage changes via continuously evolving embeddings, computed as a weighted running average of transformer-based contextualized embeddings. We demonstrate our approach on a corpus of recent New York Times article snippets and provide code for an easy to use web app to conveniently explore semantic shifts with interactive plots.
%R 10.18653/v1/2021.acl-demo.35
%U https://aclanthology.org/2021.acl-demo.35
%U https://doi.org/10.18653/v1/2021.acl-demo.35
%P 290-297
Markdown (Informal)
[Exploring Word Usage Change with Continuously Evolving Embeddings](https://aclanthology.org/2021.acl-demo.35) (Horn, ACL-IJCNLP 2021)
ACL
- Franziska Horn. 2021. Exploring Word Usage Change with Continuously Evolving Embeddings. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations, pages 290–297, Online. Association for Computational Linguistics.