In recent years, the number of industrial espionage incidents and the damage caused by them have increased. Thus, the opinion that political measures are needed to solve the problems caused by the lenient punishment of industrial espionage has emerged in our society. In this study, we used text mining and LDA topic modeling among big data analysis techniques to identify the tendency of domestic and foreign news reports containing the term ‘industrial espionage’ to identify their similarities and differences. This analysis can be used as a basis for formulating policies to respond to industrial espionage crimes. According to our analysis, domestic media mainly reported on related investigations, crimes and punishments, along with laws and systems, while foreign media mainly reported on the economic impact of industrial espionage and conflicts with China as well as Russia over attempted industrial espionage. The similarities between domestic and foreign reports include a substantial number of reports related to China, which can be interpreted as the main reason for the outflow of industrial technology in the process of securing overseas talent due to the implementation of China's Thousand Talents Plan. In addition, the difference between the respective reports was that while there were many previous studies and reports on laws and systems in Korea, there was relatively less related content in foreign countries due to the already established punishment system. Based on these findings, this study suggests policy directions such as adding a clear definition of industrial espionage to the law, adding example regulations to explain the definition, and adopting increased punitive measures proportional to the amount of damage.