%0 Conference Proceedings %T Exploring Word Usage Change with Continuously Evolving Embeddings %A Horn, Franziska %Y Ji, Heng %Y Park, Jong C. %Y Xia, Rui %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