Serial Number: http://www.riss.kr/link?id=A106287721
Title: Big Data and Classical Literature Research Methods
Author: Kim, Ba-ro & Kang, Woo-kyu
Journal: The Journal of Lang. & Lit.
Vol: 78
Pages: 7-39(33)
Published by: The Society Of Chung-Ang Lang. & Lit.
Date: 2019.
Register Information: KCI
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<Abstract>
This paper examines various digital methodologies that can be used in classical literature research, and presents the necessity and direction of big data and classical literature convergence research. Using digital analysis techniques, such as a language analysis method, network analysis method, and spatial analysis method, a new study direction of limited classical literary text can be suggested. However, existing digital analysis techniques cannot be applied to classical literary texts, and new digital analysis techniques optimized for classical literary texts need to be developed. In this situation, the direction of big data and classical literature convergence research is to build a sophisticated data model to produce meaningful knowledge. In addition, for classical literature to appreciate its own value, it is necessary to carry out continuous research and make public use plans. In this respect, we call for researchers' interest in classical literature, big data convergence research, and active sharing of classical literary data.
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