<![CDATA[This study aims to examine the most dominant aspects of computational translation studies in China and the broader international translation community with the help of CiteSpace. The primary issue addressed in this study is the divergence in research trends between Chinese academia and the global community in computational translation. This study employs CiteSpace to identify the most popular topics in computational translation studies in China and obtain an objective overview. Subsequently, it reviews 40 high-quality papers in the field to reveal the current state of research. The methodology adopted in this study involves bibliometric analysis using CiteSpace, which allows for identifying significant trends in computational translation studies. The findings indicate that contemporary research emphasizes neural networks, machine translation, and post-editing. Furthermore, there is a noticeable divergence in research interests between Chinese scholars and the international academic community. A key finding is that developing new neural models is currently a popular research focus. This study aspires to provide a clear overview of current research trends in computer-based translation studies and to identify potential areas for future exploration. By doing so, it aims to serve as a valuable guide for researchers seeking to understand the landscape of computational translation studies and to investigate emerging aspects of this ever-evolving field further]]>
Copyrights © 2025
