This study aims to explore the moral licensing behavior of listed companies in Korea using text mining. Moral licensing refers to the phenomenon of making immoral judgments or actions without guilt by giving oneself an indulgence based on past moral behavior when faced with a situation to commit immoral behavior. In the meantime, the majority of studies on moral licensing have been conducted at the individual level in the field of psychology, but this study explores the phenomenon of moral licensing at the corporate level through corporate social irresponsibility (CSiR). Specifically, this study crawled CSiR news articles of Korean listed companies that are evaluated as having high corporate social responsibility (CSR), and specifically presented CSiR behaviors through keyword extraction process and classified them by type to explore corporate moral licensing behavior. As a result of collecting CSiR news articles of Korean listed companies and extracting keywords, it was found that a company's rating change was affected by a specific CSiR rather than the number of CSiR actions throughout a given year. CSiR keywords that actually effect ratings are identified as actions that appear to have been intervened from the Fair Trade Commission, such as fines, corrective orders, subcontracting violations, and unfair trade, or socially problematic behaviors such as deaths that affect rating changes. The most collected news article was Gap-Jil, and most of the news articles belonging to Gap-Jil were an act of power against subcontractors or partners that hindered coexistence, but it was ironic in that they did not have a significant effect on the change in rating. This study is significant in that it empirically examined the abstract concept of CSiR using text mining and classified the CSiR types according to their characteristics. In addition, this study suggests implications for future improvements in ESG evaluation methods by finding out that a specific type of CSiR has a greater impact on the rating than the number of CSiR actions that actually affect the evaluation rating.