ScholarWorks@숙명여자대학교

초록

This study delves into how artificial neural network machine translation is making its way fast into our language life. The study analyzes the meaning of the news headlines, focusing on how the media helps the rapid spread of AI translation. 1,306 news cases reported from September 2016 to June 2022 were collected for the research and were later refined through a news big data providing site named BIGKinds. The refined data were then put through morphological analysis to generate a co-occurrence matrix before conducting semantic network analysis. As a result of the analyses, the keywords in those news articles turned out to be linked to value-neutral words, consisting of sub-concepts that can be divided into markets, technologies, and services. It is noteworthy that general news articles are restructured or framed by the media and gatekeepers, whereas news related to machine translation remain value-neutral. In conclusion, this study recommends that translation researchers and practitioners have a market and industry-oriented cooperation model.

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