基于自动识别的委婉语历时性发展变化与社会共变研究(A Study on the Diachronic Development and Social Covariance of Euphemism Based on Automatic Recognition)
Chenlin Zhang (张辰麟), Mingwen Wang (王明文), Yiming Tan (谭亦鸣), Ming Yin (尹明), Xinyi Zhang (张心怡)
Abstract
本文主要以汉语委婉语作为研究对象,基于大量人工标注,借助机器学习有监督分类方法,实现了较高精度的委婉语自动识别,并基于此对1946年-2017年的《人民日报》中的委婉语历时变化发展情况进行量化统计分析。从大规模数据的角度探讨委婉语历时性发展变化、委婉语与社会之间的共变关系,验证了语言的格雷什姆规律与更新规律。- Anthology ID:
- 2021.ccl-1.40
- Volume:
- Proceedings of the 20th Chinese National Conference on Computational Linguistics
- Month:
- August
- Year:
- 2021
- Address:
- Huhhot, China
- Venue:
- CCL
- SIG:
- Publisher:
- Chinese Information Processing Society of China
- Note:
- Pages:
- 435–445
- Language:
- Chinese
- URL:
- https://aclanthology.org/2021.ccl-1.40
- DOI:
- Cite (ACL):
- Chenlin Zhang, Mingwen Wang, Yiming Tan, Ming Yin, and Xinyi Zhang. 2021. 基于自动识别的委婉语历时性发展变化与社会共变研究(A Study on the Diachronic Development and Social Covariance of Euphemism Based on Automatic Recognition). In Proceedings of the 20th Chinese National Conference on Computational Linguistics, pages 435–445, Huhhot, China. Chinese Information Processing Society of China.
- Cite (Informal):
- 基于自动识别的委婉语历时性发展变化与社会共变研究(A Study on the Diachronic Development and Social Covariance of Euphemism Based on Automatic Recognition) (Zhang et al., CCL 2021)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2021.ccl-1.40.pdf