On Optimizing the Translation of Chinese Green Tea Product Description for Cross-Border Online Shops
- DOI
- 10.2991/978-2-38476-094-7_44How to use a DOI?
- Keywords
- corpus-based approach; optimization; translation of product description; Chinese green tea
- Abstract
Cross-border e-commerce platforms are one of the important channels for Chinese green tea to be sold globally, and the description of green tea products is a key factor affecting its sales. Therefore, optimizing the translation of product descriptions will positively promote the overseas sales of Chinese green tea. With a quantitative comparative analysis based on a self-built small comparable corpus, this study identified similarities and differences between the translated texts offered by Chinese vendors and the native texts offered by English-speaking vendors in the aspect of product information and textual functions, and it is proposed that the translator could resort to native texts as references to optimize their translation of product descriptions for online shops on cross-border e-commerce platforms.
- 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 - Jinyan Xu AU - Kexin Zhang AU - Liying Dong PY - 2023 DA - 2023/08/29 TI - On Optimizing the Translation of Chinese Green Tea Product Description for Cross-Border Online Shops BT - Proceedings of the 4th International Conference on Language, Art and Cultural Exchange (ICLACE 2023) PB - Atlantis Press SP - 349 EP - 361 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-094-7_44 DO - 10.2991/978-2-38476-094-7_44 ID - Xu2023 ER -