Derek Hansen

Derek L. Hansen is an Associate Professor at Brigham Young University's Information Technology program in the School of Technology (http://it.et.byu.edu/). He is also the Information Technology Program Coordinator and Abell Professor of Innovation in the School of Technology. Dr. Hansen was formerly at the University of Maryland’s iSchool where he Directed the Center for the Advanced Study of Communities and Information (http://casci.umd.edu) and was a member of the Human Computer Interaction Lab (http://www.cs.umd.edu/hcil/). Dr. Hansen completed his PhD from the University of Michigan’s School of Information where he was an NSF-funded interdisciplinary STIET Fellow (http://stiet.si.umich.edu/) focused on understanding and designing effective online socio-technical systems. His research falls in the area of user experience design, with an emphasis on social media analytics, mass collaboration, games for change, alternate reality games, citizen science, and consumer health informatics. One line of research is focused on helping analysts make sense of the mass of social data available through social media sites. He is currently working with the Social Media Research Foundation to further develop NodeXL, a network analysis and visualization tool that runs in Microsoft Excel, along with training materials for social media analysts. Another line of research applies those methods to understand best practices for supporting mass collaboration in medical, scientific, and entertainment domains. Finally, Dr. Hansen is involved with designing novel tools and activities that take advantage of the unique properties of information technologies. These include alternate reality games that promote STEM learning, "collection recommender systems," a novel "veiled viral marketing" technique that uses social networking applications (i.e., Facebook) to anonymously disseminate information about stigmatized illnesses through friendship networks, games like "Odd Leaf Out" and "Floracaching" that encourage citizen scientists to help make sense of images of plant species, and methods to predict the political tendencies of Twitter account Followers.