Enterprise risk and security management: Data, text and Web mining

The Internet, Web 2.0, consumer-generated social media, and new advanced data, text, and Web mining techniques have created tremendous business opportunities. However, the potential risk and security concerns are also equally alarming. Research of relevance to enterprise risk and security assessment and analysis has gained significant interests among MIS, CS, and business researchers. Through large-scale Web enabled content collection (e.g., corporate reports, news, consumer feedback, corporate blogs and forums, and brand sentiment) and advanced mining techniques, companies and industries will be better positioned to identify potential risks and security concerns. This special issue aimed at archiving a collection of research papers of practical and novel applications, techniques, algorithms, methods, and practices in data, text, and Web mining that will make a contribution to knowledge in enterprise risk and security management. We received 33 submissions and each paper was reviewed by two to three experts in the area. After two rounds of review, 11 highquality papers were accepted. These papers report on latest research relevant to enterprise risk and security management. The first four papers of the special issue investigated the effects of news coverage and announcements, such as those on information security investment and phishing attacks, on a company's stock price and volatility. Chai, Kim, and Rao found substantial support for their hypotheses based on the public announcements of information security investment over a 10 year period from 1997 to 2006. Despite the fact that investments in data and information security are unavoidable expenses for firms, it is difficult to measure the direct return from IT security investments. This study selected the event methodology to investigate whether information security investment announcements would affect the stock price in the market. Due to the fact that phishing attack causes financial loss and shatters the confidence of customers in conducting e-commerce, Chen, Bose, Leung and Guo adopted a hybrid approach that used text phrase extraction and supervised classification to predict the severity of a phishing attack according to its risk level or financial loss generating potential. Results indicated that the classification accuracy of the hybrid approach was quite superior, and demonstrated that the key identifying variables for risk level and potential financial loss of phishing attacks were different from each other. The usefulness of accounting numbers has been an important issue for accounting researchers and general investors. However, other information sources such as financial news may also contain useful information. Chen and his colleagues investigate how financial news impacts the return-earnings relation. The news articles in the Wall Street Journal from August 1999 through February 2007 were used to construct measures for news coverage on S&P 500 companies. This study highlighted the importance of financial news in conveying value-related information to the markets.