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Browsing by Subject "information overload"
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Item Personal Information Interfaces(Office of the Vice Chancellor for Research, 2014-04-11) Voida, Stephen; Ahmed, Ryan; Chambers, Alex; He, Xinxin; Ward, JoshuaAs the ubiquitous computing vision of “computation everywhere” has become increasingly mainstream, people make use of electronic information across multiple form factors, in more places, as part of more activities, and in more social contexts than ever before. This is the crux of the information overload problem: with a vast increase in exposure to information, there is a corresponding increase in the amount of work that people need to invest to keep up with the demands of perceiving, sense-making, organizing, utilizing, and managing that information. Dr. Stephen Voida and his student researchers in the Personal Information Interfaces (PII) laboratory explore ways that the interfaces, interaction techniques, and context-aware infrastructure employed in the next generation of information systems might better respond to the critical, real-world challenges associated with information overload. A new generation of sensor-enabled computing devices stands to magnify the information overload effect by adding streams of data about our environment, our working contexts, and traces of our activities—both online and in the real world—into the mix. A popular example is the growing number of fitness tracking devices that have appeared on the market in the last few years, for example, Fitbits, Nike+ Fuelbands, and the Jawbone Up (just to name a few). Proponents of the “quantified self” movement suggest one way to use the data streams provided by these devices: as a means for self-reflection. However, effective self-reflection requires that a vast amount of information—often highly personal in nature—be captured by our devices, and it introduces new work for end-users, such as finding patterns in the data and translating sensed trends into effective actions. We are currently launching a study of commercial fitness trackers to understand when different representations of self-reflective data streams are effective in helping to facilitate behavior change…and when those representations contribute instead to a sense of information overload. We are also exploring similar questions related to other technologies that collect and present self-reflective data about daily life—time management tools, mood-tracking apps, and the like. In general, we aim to understand how infrastructure and interface design can prevent people’s experiences of sensed data streams from contributing to information overload while still allowing us to capitalize on the positive behavior change and self-reflection potential of this information.Item Should I Stay or Should I Go: Two Features to Help People Stop An Exploratory Search Wisely(Office of the Vice Chancellor for Research, 2014-04-11) Jia, Yuan; Niu, XiAs information becomes more ubiquitously available, many information users tend to experience a sense of anxiety due to the “information overload”. Few studies have systematically examined searchers’ stopping behavior, i.e., how users recognize how much information is enough to terminate a search. Bad decisions on a stopping point will lead to either insufficient information or unnecessary waste of time and effort without much additional information gain. Understanding searchers’ stopping behavior is extremely important to assist in thorough search result evaluation and to prevent a premature or a too-late search stopping. In this study, we present the design and implementation of two search techniques: Result Preview (RP) and History Review (HR), to help people make right decisions about when to terminate a search and how to consume information efficiently when facing an overwhelming amount of information. The basic idea of RP is to visualize the distribution of newly retrieved and re-retrieved documents to users, and that of HR is to display the previous search activities for searchers to review what has been done to help define the next steps. Both features are aiming at guiding searchers through the process of problem solving and decision making about whether to stay or leave during the search process. To implement the two techniques, we developed the search system on Bing Search API. The Bing search results were brought back to the search interface using AJAX and PHP. A formal user experiment with 24 participants is also proposed to evaluate the benefits and limitations, and also inform the future RP and HR design.