Don't Jump on Hype or You Will be Dumped! Using User-Generated Content to Support Financial Market Surveillance

In this paper, an IT artifact instantiation to support decision making in the field of financial market surveillance, is presented. This artifact utilizes a qualitative multi-attribute decision model to identify situations in which prices of single stocks are affected by fraudsters who aggressively advertise the stock. A quantitative evaluation of the implemented system prototype, based on voluminous and heterogeneous data including data from social media, is provided. The empirical results indicate that that the developed IT artifact can provide support for identifying such malicious situations. Given this evidence, it can be shown that the developed solution is able to utilize massive and heterogeneous data, especially usergenerated content from financial blogs and news platforms, to provide practical decision support in the field of market surveillance.