A Quantitative Style Analysis About Different English...

Qiuying Jiang 11/03/2017 Programming for Cultural Data Analysis - Proposal A Quantitative Style Analysis about Different English Translations of the Captain’s Daughter by Alexander Pushkin Data Set The data set includes three English translations of The Captain’s Daughter (Alexander Pushkin, 1836) from Ekaterina Telfer, T. Keane and Milne Home respectively. The translation of Milne Home is downloaded from Gutenberg which is an open access project that offers free eBooks to public. The other translations are from Wikisource which serves as an online digital library of free content textual sources on a wiki. The format of the data set is txt files containing the license, source information and the literature itself. Audience and Essential†¦show more content†¦For instance, as the first Russian literature that was translated in Chinese, the Captain’s Daughter has been affecting Chinese readers and novelists from generation to generation. Besides Chinese translations, English translations of those literature also made great influence in the world. To make Pushkin’s literature enjoyed by more people, some excellent translators such as Milne Home have made great contributions. Over years, translators and translation scholars have been engaged in heated debates over salient features of the translations, strategies employed by the translators, the possible effects of the different translations and so on (Liu et al, 1997). With the involvement of statistics and natural language processing methods in literature style analysis, more and more literature scholars leverage quantitative methods to conduct their researches. According to Holmes, an analyst searches for features particularly to a given writer, features of which the writer is probably unaware and which can be measured quantitatively in order to have a basis for comparison with other writers (Holmes et al, 1985). In the case of understanding essential writing style of a writer, quantitative methods such as building and fitting of models to linguistic data and in the testing of hypotheses will definitely be good ways. In accordance with Defeng Li et al, statistical