Big-Data Analysis of Characteristics of Chinese Translation of Emily Dickinson Poems: Case Study of Student Translators' Translation Practice

Abstract

A Big-data analysis is carried out by building up relevant language corpus and applying Antconc 3.4.4, etc., to examine the characteristics of 1000 Chinese translations of 10 Emily Dickinson poems translated by 100 undergraduate students of South China University of Technology. Statistics and analysis reveal that the translation of Dickinson's poems by student translators is not faithful to the original poems, neither in form nor in content. Instead, without following the literal translation principle, student translators' translation bears distinct evidence of subjective initiative and arbitrary conduct, including altering stanza numbers and line numbers, omitting punctuation, adding modifiers to simple nouns(images), and cutting off content that is difficult to understand and translate, etc.; thus students' translation practice is more like self-fulfillment of their individual needs than a serious academic event.