A Corpus-based Study On Explicitation Of C-E Translation Of Business News-taking Global Times As An Example

In recent years,Corpus-based Translation Studies have been a focus and drawn attention of scholars.In this situation,the study of Translation Universal has been researched and valued,of which explicitation and implicitation have become the most frequent topic.The studies on explicitation have achieved a lot in the past two decades.While,reviewing previous research,the author finds that major achievements have long been confined to Indo-European languages.Relevant studies on C-E translation are still few and far between,especially for non-literary texts.This study investigates the quantity and frequency of explicitation on word number,standard type/token ratio(STTR),mean sentence length,pronouns,conjunctions and prepositions.The aim of this thesis is to verify the explicitation hypothesis in business news and attempt to figure out the reasons of explicitation and put forward some translation strategies.The author attempts to build a parallel corpus which is composed of OLC(Original Language Corpus of Chinese)and COEBN(Corpus of Translated English business news)from Global Times and a comparable corpus which include corpus COEBN(corpus of Translated English business news)from Global Times and OLE(Original Language Corpus of English)from Financial Times.By combining qualitative study and quantitative study together,the author finds that from the perspectives of words number,lexical density,pronouns and connectives,it shows obvious explicitation in translated business news texts.However,in terms of mean sentence length,there is no explicitation in translated version.In addition,for the causes of explicitation,there are language system factor,textual factor,receptor factor and cultural differences.Finally,as for the translation strategies,there are omission,addition and rewriting.