Abstract:
The Arizona Financial Text system leverages statistical learning to make trading decisions based on numeric price predictions. Research demonstrates that AZFinText outperforms the market average and performs well against existing quant funds. © 2006 IEEE.
Abstract:
The volume of qualitative data (QD) available via the Internet is growing at an increasing pace and firms are anxious to extract and understand users' thought processes, wants and needs, attitudes, and purchase intentions contained therein. An information systems (IS) methodology to meaningfully analyze this vast resource of QD could provide useful information, knowledge, or wisdom firms could use for a number of purposes including new product development and quality improvement, target marketing, accurate "user-focused" profiling, and future sales prediction. In this paper, we present an IS methodology for analysis of Internet-based QD consisting of three steps: elicitation; reduction through IS-facilitated selection, coding, and clustering; and visualization to provide at-a-glance understanding. Outcomes include information (relationships), knowledge (patterns), and wisdom (principles) explained through visualizations and drill-down capabilities. First we present the generic methodology and then discuss an example employing it to analyze free-form comments from potential consumers who viewed soon-to-be-released film trailers provided that illustrates how the methodology and tools can provide rich and meaningful affective, cognitive, contextual, and evaluative information, knowledge, and wisdom. The example revealed that qualitative data analysis (QDA) accurately reflected film popularity. A finding is that QDA also provided a predictive measure of relative magnitude of film popularity between the most popular film and the least popular one, based on actual first week box office sales. The methodology and tools used in this preliminary study illustrate that value can be derived from analysis of Internet-based QD and suggest that further research in this area is warranted.
Abstract:
This article presents an exploratory study of jihadi extremist groups' videos using content analysis and a multimedia coding tool to explore the types of video, groups' modus operandi, and production features that lend support to extremist groups. The videos convey messages powerful enough to mobilize members, sympathizers, and even new recruits to launch attacks that are captured (on video) and disseminated globally through the Internet. They communicate the effectiveness of the campaigns and have a much wider impact because the messages are media rich with nonverbal cues and have vivid images of events that can evoke not only a multitude of psychological and emotional responses but also violent reactions. The videos are important for jihadi extremist groups' learning, training, and recruitment. In addition, the content collection and analysis of extremist groups' videos can help policymakers, intelligence analysts, and researchers better understand the extremist groups' terror campaigns and modus operandi, and help suggest counterintelligence strategies and tactics for troop training.
