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The Firm Life Cycle Forecasting Model Using Machine Learning Based on News Articles
- Lee, Si Young;
- Oh, Sae Yong;
- Lee, Sangwook;
- Gim, Gwang Yong
WEB OF SCIENCE
4SCOPUS
2초록
The determination of the firm life cycle has been carried out in relation to the establishment of corporate strategy in the field of accounting or management. The life cycle prediction based on financial information is long because it is determined based on the financial performance of the entity over a year. This study sought to lay the foundation for overcoming this by using news articles to predict the life cycle of a company. In the process of quantifying news article data and predicting the firm life cycle, the method of selecting keywords that can represent the firm life cycle is presented, and the life cycle prediction model is verified with four machine learning techniques using selected candidate keywords. In this study, all four machine learning techniques showed a predicted static classification rate of nearly 60%, demonstrating the availability of news articles, which are unstructured text data, in predicting the corporate life cycle. (C) 2021 The Authors. Published by Atlantis Press B.V.
키워드
- 제목
- The Firm Life Cycle Forecasting Model Using Machine Learning Based on News Articles
- 저자
- Lee, Si Young; Oh, Sae Yong; Lee, Sangwook; Gim, Gwang Yong
- 발행일
- 2021-01
- 유형
- Article
- 저널명
- INTERNATIONAL JOURNAL OF NETWORKED AND DISTRIBUTED COMPUTING
- 권
- 9
- 호
- 1
- 페이지
- 1 ~ 9
- 언어
- ENG
- 출판사
- ATLANTIS PRESS
- 발행국가
- 프랑스
- 분량
- 9 페이지
- ISSN
- E 2211-7946
P 2211-7938