2017-2025년 중국 기계번역 메타연구 - CNKI 데이터 기반 계량서지학적 접근
Meta-Research on Machine Translation in China (2017–2025): A Bibliometric Study Based on CNKI Data
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This study conducts a bibliometric analysis of machine translation (MT) papers published in China from 2017 to the first half of 2025, offering a comprehensive review of research trends and topic-specific characteristics. The results reveal a multilayered developmental trajectory: research that began with a technology-centered focus has progressively expanded to comparative error analysis, human collaboration, pedagogy, and, ultimately, translation ethics. The findings further indicate that Chinese MT research has moved beyond a purely technical-analytic phase toward an integrated research environment that links technology, education, ethics, and service. In particular, since 2023, the emergence of systems such as ChatGPT and DeepSeek has broadened “AI translation” beyond NMT-centered technical debates to encompass collaboration, education, evaluation, and ethics; moreover, generative AI is transforming not merely translation quality but the very meaning of translational practice. Accordingly, translator agency, evaluation standards, and pedagogical orientations are being reconfigured in tandem.
Abstract
This study conducts a bibliometric analysis of machine translation (MT) papers published in China from 2017 to the first half of 2025, offering a comprehensive review of research trends and topic-specific characteristics. The results reveal a multilayered developmental trajectory: research that began with a technology-centered focus has progressively expanded to comparative error analysis, human collaboration, pedagogy, and, ultimately, translation ethics. The findings further indicate that Chinese MT research has moved beyond a purely technical-analytic phase toward an integrated research environment that links technology, education, ethics, and service. In particular, since 2023, the emergence of systems such as ChatGPT and DeepSeek has broadened “AI translation” beyond NMT-centered technical debates to encompass collaboration, education, evaluation, and ethics; moreover, generative AI is transforming not merely translation quality but the very meaning of translational practice. Accordingly, translator agency, evaluation standards, and pedagogical orientations are being reconfigured in tandem.