A comparative study with text mining: "Le Petit Prince" translations

The aim of this study is to test the usability and adequacy of KH Coder, a text mining analysis tool, in translation comparison studies in the light of "equivalence" and "matricial norms". Text mining is a method that accepts natural language text as a data source and aims to obtain structured data through text. KH Coder is a software that can be used in text mining as well as computational linguistics and quantitative content analysis studies and can directly process and analyse data. "Matricial norms", one of the translation norms suggested by Gideon Toury, are norms that guide how the formal values of the source text will be included in the target text and how much they will be changed and cover formal changes such as all kinds of substitutions, additions and deletions in the text. On the other hand, "equivalence" can be determined by two different concepts: "adequacy" and "acceptability". The translation is considered an "adequate" translation if it is close to the source system, and an "acceptable" translation if it is close to the target system. In this study, Antoine de Saint-Exupéry's work "Le Petit Prince" and its translations of "The Little Prince" in English, "星の王子さま" (Hoshi no Ōjisama) in Japanese and "Маленький принц" (Malen'kij Princ) in Russian were considered as the objects of study. Firstly, the objects of analysis were organised in Excel file format, then they were introduced to KH Coder and the findings of the analysis were extracted. In the first part of the analysis, the findings were interpreted, and in the second part, the findings were compared in theoretical context. At the end of the study, it was observed that KH Coder was usable and sufficient in translation comparison studies carried out in the context of matricial norms and equivalence.