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Korea Society of IT Services (한국IT서비스학회)
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A Study on Effective Sentiment Analysis through News Classification in Bankruptcy Prediction Model

부도예측 모형에서 뉴스 분류를 통한 효과적인 감성분석에 관한 연구

  • 김찬송 (한양대학교 일반대학원 비즈니스 인포매틱스학과) ;
  • 신민수 (한양대학교 경영학부)
  • Received : 2018.01.31
  • Accepted : 2019.01.10
  • Published : 2019.03.31
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Abstract

Bankruptcy prediction model is an issue that has consistently interested in various fields. Recently, as technology for dealing with unstructured data has been developed, researches applied to business model prediction through text mining have been activated, and studies using this method are also increasing in bankruptcy prediction. Especially, it is actively trying to improve bankruptcy prediction by analyzing news data dealing with the external environment of the corporation. However, there has been a lack of study on which news is effective in bankruptcy prediction in real-time mass-produced news. The purpose of this study was to evaluate the high impact news on bankruptcy prediction. Therefore, we classify news according to type, collection period, and analyzed the impact on bankruptcy prediction based on sentiment analysis. As a result, artificial neural network was most effective among the algorithms used, and commentary news type was most effective in bankruptcy prediction. Column and straight type news were also significant, but photo type news was not significant. In the news by collection period, news for 4 months before the bankruptcy was most effective in bankruptcy prediction. In this study, we propose a news classification methods for sentiment analysis that is effective for bankruptcy prediction model.

Keywords

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Research Model for Sentiment Analysis that is Effective in Bankruptcy Prediction

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Data Pre-Processing and Sentiment Dictionary Building Process

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Artificial Neural Network Model

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Collection Period of News

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Sensitivity Graph According to News Collection Period

Types of News Previous Research

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Altman's Financial Ratio Variable

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Top 20 Words by Frequency

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Examples of Corpus-based Sentimental Dictionary Words

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The Number and Percentage of News Types

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Prediction Accuracy of the News Type to Bankruptcy Prediction

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Prediction Sensitivity of the News Type to Bankruptcy Prediction

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Prediction Results Using News Gathering Period and Financial Ratios

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t-Test Result of News Type Variable

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t-Test Result of Financial Ratio Variable

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