A corpus-based study of Howard Goldblatt’s translation style in his English rendering of the Shanhaijing
Wen Zhong () and
Minghui Long ()
International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 3, 817-825
Abstract:
The classic work, Shanhaijing, is a seminal work in ancient Chinese literature, celebrated for its mysticism and profound depth. Its English translation plays a pivotal role in helping the international community understand Chinese mythological culture, and an analysis of its translation style can offer valuable insights and references for the translation of similar classical texts. Therefore, this study aims to examine Howard Goldblatt’s English translation of Shanhaijing, focusing on his translational style and its effect on the comprehension of English-speaking readers. Utilizing corpus tools such as WordSmith, AntConc, and Readability Analyzers, the study conducts a quantitative comparison of translations by Goldblatt, Anne Birrell, and Wang Hong. The analysis combines literature review and corpus-based methods to examine Goldblatt’s translation style in terms of word frequency, type-token ratio, mean word and sentence length, and readability. The research reveals that Goldblatt demonstrates a rich lexical variety, employing straightforward yet precise and nuanced syntax. Overall, Howard Goldblatt successfully preserved the cultural essence of the original text while enhancing the expressiveness and richness of the translation, thereby deepening English readers’ understanding and appreciation of this classic work. The findings provide significant guidance for the international communication of classical texts and offer effective approaches on how to make classic works more accessible to international readers.
Keywords: Corpus linguistics; cross-cultural communication; Shanhaijing; stylistic analysis; translation strategies. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:aac:ijirss:v:8:y:2025:i:3:p:817-825:id:6616
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