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Text Mining for Economic Analysis (in Korean)

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Soohyon Kim & Youngjoon Lee & Jhinyoung Shin & Ki Young Park, 2019. "Text Mining for Economic Analysis (in Korean)," Working Papers 2019-18, Economic Research Institute, Bank of Korea.
    • Handle: RePEc:bok:wpaper:1918
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    More about this item

    Keywords

    Text Mining; Machine Learning; Economic Analysis;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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