Behavioral Modeling and Prediction with Wearable and Mobile Devices
Emerging trends in smartphones and wearable devices (smartwatches, fitness trackers) allow for creation of a rich user behavioral profile for users as they engage in search tasks. Such a behavioral (social, mobile, affective, and cognitive) profile goes beyond traditional browser-based context and allows one's personality type and social capital to become pivotal predictors of search behavior and performance. We are working on collecting and analyzing data from wearable and mobile devices, in addition to the Web logs and social media streams, to identify various behavioral markers. This could help us understand individuals at a level not possible before. The new knowledge gained by this could help us predict various behavioral patterns about an individual, including their searching/browsing and consumption behaviors. For instance, we may find that one's social capital is positively correlated to one's ability to cover novel information, but negatively correlated to one's overall search performance. We may find that when an extrovert collaborates with an introvert, they have a higher likelihood of learning and unique coverage than extrovert-extrovert or introvert-introvert pairs.