Analysis of Information Security News Content and Abnormal Returns of Enterprises

Autor: Chia-Ching Hung
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Big Data and Cognitive Computing, Vol 3, Iss 2, p 24 (2019)
Druh dokumentu: article
ISSN: 2504-2289
DOI: 10.3390/bdcc3020024
Popis: As information technologies and the Internet have rapidly evolved, businesses have begun to use them to improve communication efficiency within and outside the organization. However, applications of information technologies are accompanied by information delivery, personal data protection, and information security problems. There are potential risks inherent in any application of information technologies. Moreover, with the improvement of networking and computing capabilities, the impact of attacks from hackers and malicious software has also increased. A breach or leakage of important corporate data may not only damage the firm’s image but also sabotage the firm’s operation, resulting in financial losses. In this study, the content of information security news reports was analyzed in an attempt to clarify the association between information security news and corporate stock prices. Methods including decision trees, support vector machines (SVMs), and random forests were used to explore the associations of news related variables with abnormal returns. Results indicate that the news source and the presence of negative words in the news have an impact on abnormal returns.
Databáze: Directory of Open Access Journals