Neural Machine Translation Research Progress and Its Implications for Education Technology: A Bibliometric Analysis
Qingbo Jiang, Yong Huang · 2023
Neural machine translation (NMT) stands as one of the most prominent domains in contemporary natural language processing research. In this study, employing VOSviewer software, we conducted a bibliometric analysis based on 1386 NMT-related publications retrieved from the Web of Science database as of September 2023. Co-citation analysis revealed that influential sources in the NMT field were primarily concentrated in top-tier conferences and journals in areas such as artificial intelligence, neural computing, and computer vision. Notably influential authors focused on machine translation techniques, deep learning, and natural language processing technologies. Co-occurrence analysis delineated two prominent research directions within the NMT domain: machine translation and deep learning. Based on the outcomes of bibliometric analysis, we provide insights into the current state, challenges, and prospects of NMT research and offer an understanding of NMT applications in the realm of educational technology.