Comparative Analysis Of Translated And Native Chinese In Economy And Management Texts

Translation Universals is an important concept in the field of translation studies,referring to certain translation phenomena or features that are commonly found in different languages,cultural backgrounds and translated texts.These include simplification,explicitation,normalization,levelling out,source language interference and underrepresentation of target language unique items.Since the 1990s,translation scholars have been extensively researching translation universals,particularly simplification and explicitation.However,most studies have focused on literary texts in English or other closely related Indo-European languages,with fewer studies addressing other subjects and language families.Moreover,there has been limited research on newly proposed translation universal hypotheses,such as levelling out,source language interference and under-representation of target language unique items.The study aims to explore the features of translated Chinese in order to understand the applicability of the six English-based translation universal hypotheses to Chinese.Thirty original Chinese texts on economy and management,along with thirty Chinese texts translated from English on the same subject,were selected to create a comparable Chinese corpus.To process,analyze and manage the corpus and data,various tools were employed,such as the Python package "jieba",Microsoft Excel and SPSS Statistics.After obtaining data that revealed differences between the two sub-corpora,further normality tests and independent sample t-tests were conducted to determine whether the differences were statistically significant.The results show that compared to the native Chinese sub-corpus,the translated one exhibits a lower lexical density and standard deviation for the majority of relevant indicators,higher frequencies of conjunctions,auxiliaries,pronouns and full stops,and lower frequencies of commas and pause marks.Additionally,the translated sub-corpus has a higher proportion of the most frequent words,as well as a higher repetition rate of veryhigh frequency words.Based on these findings,it can be concluded that levelling out is generally supported;simplification,explicitation,source language interference and underrepresentation of target language unique items are partially supported;while normalization is entirely rejected.