A COMPUTERISED ANALYSIS OF TRANSLATION REGULARITIES (BASED ON A UKRAINIAN-LANGUAGE COMPARABLE CORPUS OF FICTION)
Abstract
The article focusses on computerised analysis of translation regularities in the target text. The study used the Ukrainian Comparable Corpus of fictional texts, comprising 4 million tokens and including a subcorpus of original texts (UOC) consisting of 100 prosaic texts by Ukrainian authors, and a subcorpus of 100 English-language prosaic texts translated into Ukrainian (UTC). Both subcorpora contained 20,000 tokens each. The work uses general scientific research methods – the hypothetical-deductive method, methods of analysis and synthesis, the comparative analysis method, the descriptive method; methods of computer analysis: quantitative analysis of linguistic data from research corpora based on the Linguistic Inquiry and Word Count (LIWC2015) text diagnostics computer program, SPSS 26 computer software – Student’s t-test for dependent and independent samples, and Mann-Whitney’s nonparametric U-test. The results showed that the tendency towards implicitation, complication, and derationalization was the dominant regularity in the target texts. These and other phenomena are described at the morphological, lexical, syntactic, stylistic, and pragmatic levels. In particular, at the morphological level, there is explicitation: the proportion of pronouns increased in the UTC subcorpus compared to the UOC subcorpus. At the stylistic level, there is simplification: the proportion of negative constructions decreased in the UTC subcorpus. At the lexical level, there is a tendency towards levelling out, which consists in avoiding “exoticisation” and reducing the proportion of colloquial units. At the syntactic level, there is implicitation: a decrease in the mean rank of conjunctions and prepositions, as well as derationalization: a decrease in the weight of causality markers. At the pragmatic level, there is normalisation: a decrease in the mean rank of discourse markers-fillers and pragmatic markers—interjections and particles. The quantitative data obtained are duly visualised and presented in tables. It has been established that the aforementioned deformations make the corpus of Ukrainian translations more cognitively “overloaded,” more complex, more formalised, and less logically coherent. We see prospects for further research to clarify the causes of text coherence deformation in translation across a broader range of source material. In this case, the UCC should include literary prose texts across many functional, stylistic, and genre varieties, as well as translations that reflect the individual style of the translators.
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