@inproceedings{e748808be06c42bc86b10f9d39ed2cbb,
title = "Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese",
abstract = "Recent research has brought a wind of using computational approaches to the classic topic of semantic change, aiming to tackle one of the most challenging issues in the evolution of human language. While several methods for detecting semantic change have been proposed, such studies are limited to a few languages, where evaluation datasets are available. This paper presents the first dataset for evaluating Chinese semantic change in contexts preceding and following the Reform and Opening-up, covering a 50-year period in Modern Chinese. Following the DURel framework, we collected 6,000 human judgments for the dataset. We also reported the performance of alignment-based word embedding models on this evaluation dataset, achieving high and significant correlation scores.",
author = "Jing Chen and Emmanuele Chersoni and Huang, \{Chu Ren\}",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 3rd International Workshop on Computational Approaches to Historical Language Change, LChange 2022 ; Conference date: 26-05-2022 Through 27-05-2022",
year = "2022",
month = may,
doi = "10.18653/v1/2022.lchange-1.11",
language = "English",
series = "LChange 2022 - 3rd International Workshop on Computational Approaches to Historical Language Change 2022, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "113--118",
editor = "Nina Tahmasebi and Syrielle Montariol and Andrey Kutuzov and Simon Hengchen and Haim Dubossarsky and Lars Borin",
booktitle = "LChange 2022 - 3rd International Workshop on Computational Approaches to Historical Language Change 2022, Proceedings of the Workshop",
address = "United States",
}