Application of the Search Engine Google as Big Data in Translation Studies
Cho Joon-Hyung, Lee Hye-Won · 2018
From the 1960s, the corpus became the resources in the field of linguistics for the practical studies. Translation studies also accepted this type of study to explain translational phenomena. Since Gideon Toury and Mona Baker proposed the application of corpus in this field, various translation corpora are used to extract translational correspondences for several studies such as translational comparison between two languages, translation education, machine translation, etc. However, a complete corpus needs a lot of time and cost. Moreover, in Korea, there is no big corpus of translation like the website Linguee. From this point of view, we can consider the search engine Google as Big Corpus. Although it is not a parallel corpus, we are able to profit translational correspondences from Google as Big corpus because it may provide quite a number of textual translation resources between Korean and other languages.