A Corpus-Based Study on Liu Yukun’s Translation Style as Reflected in Folding Beijing
- DOI
- 10.2991/978-94-6463-040-4_27How to use a DOI?
- Keywords
- Corpus Technology; Quantitative Analysis; Sci-Fi Translation; Folding Beijing
- Abstract
Folding Beijing, written by Hao Jingfang and later translated by the famed science fiction writer Liu Yukun (also known as Ken Liu), has been a hit overseas, promoting the spread of Chinese culture and winning the Hugo Award for Best Novelette in 2016. This paper will take Liu Yukun’s translation as an example, using quantitative and qualitative methods to analyze Liu Yukun’s translation style. The corpus technology, the software Antconc, is used to construct the self-built corpus of Folding Beijing translated by Liu Yukun. And then the data analysis is expounded from the aspects of standard type-token ration (STTR), lexical density and word frequency, average sentence length and passive voice sentences, and narrative tenses. Based on the big data and corpus technology, it is found that the translation of Folding Beijing is basically faithful to the original text, and at the same time has its own unique style, which is close to the habits of the target language.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yuting Chen AU - Wei Gong PY - 2022 DA - 2022/12/27 TI - A Corpus-Based Study on Liu Yukun’s Translation Style as Reflected in Folding Beijing BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 178 EP - 184 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_27 DO - 10.2991/978-94-6463-040-4_27 ID - Chen2022 ER -