A Text Mining Approach to ‘Operational Norms’

Abstract

The notion of 'translation norms' was introduced by Gideon Toury in the late 1970s within Descriptive Translation Studies (DTS). Toury's endeavor was to describe and explain translations to make generalizations regarding translational behavior. Due to the exhaustive nature of such attempt, analysis of everything is deemed 'untenable' by Toury, and even sampling is limited to the capacity of human effort. This paper 1 argues that exhaustive analysis on 'operational norms' can be facilitated through text mining. Text mining is a term that can be described as automated analysis of text data aided by a software to extract and discover new insights. As part of this study, a custom-made software tool is designed, and the corpus of a master's thesis (Duymaz 2020) is used as a reference point to analyze and compare the findings with a view to testing the effectiveness of the software versus human effort. The tool is designed by a software expert, and then the test data is subjected to a preparation stage to achieve optimal results by the software. After processing the test data, operational norms are extracted to be interpreted. The analysis has provided results that cannot be obtained by sole human effort, enabling researchers to have further insights about translations. This research thus has a potential for making a notable contribution to DTS. Further studies will improve the tool verifying its viability for various text types to ensure such contribution.