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http://dx.doi.org/10.7472/jksii.2021.22.5.79

Machine Learning based Firm Value Prediction Model: using Online Firm Reviews  

Lee, Hanjun (Department of Management Information Systems, Myongji University)
Shin, Dongwon (Industry Academic Cooperation Foundation, Myongji University)
Kim, Hee-Eun (College of Business Administration, Myongji University)
Publication Information
Journal of Internet Computing and Services / v.22, no.5, 2021 , pp. 79-86 More about this Journal
Abstract
As the usefulness of big data analysis has been drawing attention, many studies in the business research area begin to use big data to predict firm performance. Previous studies mainly rely on data outside of the firm through news articles and social media platforms. The voices within the firm in the form of employee satisfaction or evaluation of the strength and weakness of the firm can potentially affect firm value. However, there is insufficient evidence that online employee reviews are valid to predict firm value because the data is relatively difficult to obtain. To fill this gap, from 2014 to 2019, we employed 97,216 reviews collected by JobPlanet, an online firm review website in Korea, and developed a machine learning-based predictive model. Among the proposed models, the LSTM-based model showed the highest accuracy at 73.2%, and the MAE showed the lowest error at 0.359. We expect that this study can be a useful case in the field of firm value prediction on domestic companies.
Keywords
Firm value; Machine learning; Online review; Firm review; Jobplanet;
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