Status and Trends of Research on China’s Machine Translation— CiteSpace-Based Visual Bibliometric Analysis (2020–2025)

Abstract

Machine translation is a language processing technology and cross-lingual intelligent task, which adopts computer algorithms and artificial intelligence to automatically transform text between different natural languages without manual sentence-by-sentence participation. In recent years, machine translation has been increasingly widely applied in translation practice, and relevant research has gradually become a popular academic hotspot. As a typical representative intelligent technological application in the fields of artificial intelligence and language services in China, machine translation is of vital importance to grasping the developmental context and evolutionary pattern of China’s artificial intelligence industry and language service sector, From the perspective of development trends, machine translation research is expected to remain a cutting-edge topic in translation studies. Based on 497 research papers published in CNKI during the research period, this paper adopts the CiteSpace information visualization software. From five dimensions including authors, research institutions, burst keywords, keyword relevance and timeline, it focuses on research hotspots and development trends, conducts a systematic analysis of domestic literature in the field of machine translation in China, and summarizes the research focuses and frontier trends in this domain. Using CiteSpace as the visualization analysis tool, this study finds that domestic machine translation research from 2020 to 2025 presents the following characteristics: it is led by core authors yet lacks adequate team collaboration; foreign language universities and top research institutions occupy a dominant position, and regional features have formed distinctive research clusters. The main research line remains stable, the research on human-machine relationship keeps advancing, and interdisciplinary features are becoming increasingly prominent. Research hotspots have been upgraded in technology, application scenarios and translation quality, forming a research pattern featuring the linkage of technology, process and data as well as the in-depth integration of industry, academia and research. Meanwhile, this study also predicts the potential development trends of machine translation in such directions as intelligent human-machine collaborative translation, multimodal translation, and the application of large language model-based translation.