• Title/Summary/Keyword: R 텍스트 마이닝

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Quantitative Text Mining for Social Science: Analysis of Immigrant in the Articles (사회과학을 위한 양적 텍스트 마이닝: 이주, 이민 키워드 논문 및 언론기사 분석)

  • Yi, Soo-Jeong;Choi, Doo-Young
    • The Journal of the Korea Contents Association
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    • v.20 no.5
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    • pp.118-127
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    • 2020
  • The paper introduces trends and methodological challenges of quantitative Korean text analysis by using the case studies of academic and news media articles on "migration" and "immigration" within the periods of 2017-2019. The quantitative text analysis based on natural language processing technology (NLP) and this became an essential tool for social science. It is a part of data science that converts documents into structured data and performs hypothesis discovery and verification as the data and visualize data. Furthermore, we examed the commonly applied social scientific statistical models of quantitative text analysis by using Natural Language Processing (NLP) with R programming and Quanteda.