Hamid Abbaskhani - Department of accounting
Asgar Pakmaram - Department of Accounting, Bonab Branch, Islamic Azad University, Bonab, Iran
Nader Rezaei - Department of Accounting, Bonab Branch, Islamic Azad University, Bonab, Iran
Jamal Bahri Sales - Department of Accounting, Urmia Branch, Islamic Azad University, Urmia, Iran

Despite the growing need for research on the going concern and bankruptcy of companies, most of the conducted studies have used the approach of quantitative data for predicting the going concern and bankruptcy of companies; on the other hand, it is possible to manage these quantitative data by company managers. As a result, there appears to be a need to examine alternative methods for predicting going concern and bankruptcy based on qualitative data from the auditor's report. The purpose of this research is to determine the ability to predict the going concern of the companies using quantitative and qualitative data. The study period was from ۲۰۱۱ to ۲۰۲۱, with a sample of ۵۴ companies admitted to the Tehran Stock Exchange. The results of the first hypothesis test show that the coefficient of determination of text-mining approach model prediction with the presence of a life cycle variable is greater than the determination coefficient of text-mining approach model prediction with the presence of a company size variable. The test of the second hypothesis shows that the difference in the increasing explanatory power of the first model compared to the second model in the companies accepted in the stock exchange is significant.

Financial Forecasting, Going Concern, Tone Analysis, Auditor Reporting