Using neural topic models to track context shifts of words: a case study of COVID-related terms before and after the lockdown in April 2020

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Metadaten
Author:Olga Kellert, Md Mahmud Uz ZamanGND
URN:urn:nbn:de:bvb:384-opus4-1117155
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/111715
ISBN:978-1-955917-42-1OPAC
Parent Title (English):Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, May 26-27, 2022, Dublin, Ireland
Publisher:Association for Computational Linguistics (ACL)
Place of publication:Stroudsburg, PA
Editor:Nina Tahmasebi, Syrielle Montariol, Andrey Kutuzov, Simon Hengchen, Haim Dubossarsky, Lars Borin
Type:Conference Proceeding
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2024/02/29
First Page:131
Last Page:139
DOI:https://doi.org/10.18653/v1/2022.lchange-1.14
Institutes:Philologisch-Historische Fakultät
Philologisch-Historische Fakultät / Angewandte Computerlinguistik
Philologisch-Historische Fakultät / Angewandte Computerlinguistik / Lehrstuhl für Angewandte Computerlinguistik (ACoLi)
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)