A text mining approach to the analysis of information security awareness: Korea, United States, and China

Recently in Korea, the importance of information security awareness has been receiving a growing attention. Attacks such as social engineering and ransomware are hard to prevent because it cannot be solved by information security technology. Also, the profitability of information security industry has been decreasing for years. Because of this, many companies try to find a new growth-engine and an entry to the foreign market. The main purpose of this paper is to draw out some information security issues that people of each country think and to analyze it. Finally, this study identifies issues and suggests how to improve the situation in Korea. For this, Topic Modeling analysis has been used to find information security issues of each country. Moreover, the score of sentiment analysis has been used to compare each country. The study contributes to the literature by exploring and explaining what critical issues are and how to improve the situation based on the identified issues of the Korean information security industry. Also, this study adds to the literature by demonstrating how text mining can be applied to the context of information security awareness. From a pragmatic perspective, the study has the implications for information security enterprises. This study is expected to provide a new and realistic method of analyzing domestic and foreign issues using the analyzing real data of the Twitter API.