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Applications of the Text Mining Approach to Online Financial Information

첫 페이지 보기
  • 발행기관
    한국경영정보학회 바로가기
  • 간행물
    Asia Pacific Journal of Information Systems KCI 등재 SCOPUS 바로가기
  • 통권
    제32권 제4호 (2022.12)바로가기
  • 페이지
    pp.770-802
  • 저자
    Hansol Lee, Juyoung Kang, Sangun Park
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A423717

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원문정보

초록

영어
With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.

목차

ABSTRACT
Ⅰ. Introduction
1.1. Research Background
1.2. Research Objectives
Ⅱ. Literature Review
2.1. Characteristics of Textual Data and Text Mining
2.2. Text Mining Research Procedure
2.3. Text Mining Applications in Finance
Ⅲ. Text Mining Techniques for Financial Information
3.1. Preparation of Financial Textual Data
3.2. Keyword Analysis of Financial Textual Data
3.3. Natural Language Processing Application Using Machine Learning for Financial Textual Data
Ⅳ. Empirical Case Study of Text Mining in Financial Information
4.1. Text Mining Applications to “Government Finance” from News Articles
4.2. Text Mining on “Free Education” from News Articles
Ⅴ. Topics for Future Financial Research Using Text Miming
5.1. Building a Corpus of Financial Information
5.2. Detecting Financial Execution Anomalies
5.3. Evaluation of Policy Programs
5.4. Discovering Policy Blind Spots
5.5. Support for Budget Planning
Ⅵ. Conclusion and Contribution
6.1. Conclusion
6.2. Discussions and Contributions
Acknowledgements


키워드

Text Mining Finance Fiscal Policy Financial Information Keyword Analysis Social Network Analysis Sentiment Analysis Topic Modeling Machine Learning

저자

  • Hansol Lee [ Assistant Professor, School of Business, Ajou University, Korea ]
  • Juyoung Kang [ Professor, School of Business, Ajou University, Korea ] Corresponding Author
  • Sangun Park [ Professor, Department of MIS, Kyonggi University, Korea ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국경영정보학회 [The Korea Society of Management information Systems]
  • 설립연도
    1989
  • 분야
    사회과학>경영학
  • 소개
    이 학회는 경영정보학의 연구 및 교류를 촉진하고 학문의 발전과 응용에 공헌함을 목적으로 합니다.

간행물

  • 간행물명
    Asia Pacific Journal of Information Systems
  • 간기
    계간
  • pISSN
    2288-5404
  • eISSN
    2288-6818
  • 수록기간
    1990~2026
  • 등재여부
    KCI 등재,SCOPUS
  • 십진분류
    KDC 325 DDC 658

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