Text Mining for Economic Analysis (in Korean)
Soohyon Kim (),
Youngjoon Lee (),
Jhinyoung Shin () and
Ki Young Park ()
Additional contact information
Soohyon Kim: Economic Research Institute, Bank of Korea
Youngjoon Lee: Precourt Institute for Energy, Stanford University
Jhinyoung Shin: Yonsei Business School
Ki Young Park: Yonsei School of Economics
No 2019-18, Working Papers from Economic Research Institute, Bank of Korea
We provide detailed description of how text data analysis is done and review series of studies done through text mining. Natural language can be characterized with ambiguity and obscurity compared to structured data. It is hard to retrieve useful information from text data as it carries natural language itself. Text mining or natural language processing is a multi-discipline area of modern technic in which we can distill and obtain just what we need from text. With the development of AI and machine learning, text mining is becoming one of the high-end technology in various fields of research even in economics. We expect there will be more demand for text data analysis as it will be complementary to traditional structured data and also as a new source of information.
Keywords: Text Mining; Machine Learning; Economic Analysis (search for similar items in EconPapers)
JEL-codes: A12 B41 C80 (search for similar items in EconPapers)
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