Abstract
ABSTRACTRecent years has seen a steady development of translation quality research. This paper, with the help of Bicomb (for co-word analysis), UCINET（for social network analysis）, and SPSS21.0 (for cluster analysis), has made a detailed exploration of papers on translation quality in CNKI (China National Knowledge Infrastructure) in terms of the number of papers, journal distribution, high-frequency key words, and diachronic change of key words that may help to reflect research topics and trends in the Chinese mainland in the past two decades. It also offers recommendations for further study and provides some insights for researchers on translation quality.
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