AI REVOLUTION IN LITERARY TRANSLATION: A BIBLIOMETRIC ANALYSIS OF TRENDS, CHALLENGES, AND POTENTIALS

Abstract

AI has significantly affected literary translation through tools such as Neural Machine Translation and Large Language Models, providing greater speed and accessibility. However, their grasp of literary subtleties, like metaphor, tone, and culture, remains subject to debate. This study uses a bibliometric analysis of 254 peer-reviewed articles from 2005 to 2025 in the Scopus database, employing OpenRefine, VOSviewer, and Scopus Analyser. Findings indicate a surge in publications after 2020, reaching a peak in 2024. Most research comes from technical disciplines; Computer Science (26.6%), Engineering (21.7%), and Mathematics (10.3%), with limited input from the Arts and Humanities (1.8%). China leads in publications (41.3%), followed by India and the U.S. Keyword analysis reveals a focus on AI methods, often neglecting translation-specific challenges. The study calls for interdisciplinary collaboration and culturally sensitive AI to preserve literary depth.