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Applications of the Text Mining Approach to Online Financial Information

원문정보

Hansol Lee, Juyoung Kang, Sangun Park

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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


저자정보

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

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