I am currently studying HCI and information visualization at the University of Michigan School of Information with advisor Eytan Adar. I began my phd in 2009. I have an M.S.I. in Information Analysis & Retrieval from the University of Michigan School of Information as well as an M.F.A. (Experimental Poetics and Prose) from the Jack Kerouac School for Disembodied Poetics at Naropa University.
I am passionate about increasing the efficiency of groups and individual analysis and communication with information visualizations in online settings, such as crowdsourced visual analysis and data storytelling. The popularity of information visualizations online by non-domain experts has the potential to generate useful analytic insights into scientific and organizational data, improved understanding of news and social issues, and engaging new data presentations created by end users of visualization tools. Yet the usefulness of visualizations can be threatened by risks to accurate interpretation imposed by perceptual properties of the graph design, individual differences in graph and statistical literacy, cognitive biases, and social influences. As a researcher in visualization I work to identify innovative ways in which to improve non-domain expert analysis and communication with data and graphs so as to increase both individual and collective accuracy.
Topics I've worked on include studying the effects of social influences on individual and group level accuracy in crowdsourced visual analysis, creating a system for automatic creation of annotated narrative visualizations, showing how adding "desirable difficulties" to learning from visualizations can improve understanding, as well as describing how designers of online storytelling visualizations use framing techniques to persuade users. Find out more about current and past research here.
To contact me directly, email me at jessica dot hullman at gmail or jhullman at umich dot edu.