Decoding the digital: a corpus-based study of simplifications and other translation universals in translated texts.

Translation universals have garnered significant interest across disciplines such as translation studies, linguistics, and machine translations. However, their exploration remains relatively underrepresented within the realm of technology and computing. Leveraging statistical analyses, principal component assessment, and advanced visualization tools, this study delves into translation universals found within a novel corpus of articles, originally from English journals and magazines, translated by Chinese computing experts. This exploration discerns overarching patterns, termed translation universals, along with nuances distinctive to the computing sector. Furthermore, the research offers theoretical insights into the impetuses guiding such translations, anchored by the entropy theory, the Principle of Least Effort, and the Principle of Relevance. Notably, while the translated versions manifest a higher type-token ratio than their native Chinese counterparts, characteristics of simplification and explicitation remain salient in the translated Chinese text.