University of Michigan Professor of Information Paul Resnick presents on RumorLens, a suite of tools designed to help journalists and the public identify new rumors on Twitter. He explains how automated learning and computation enhances these tools, behind the scenes, and the three different elements of the processing pipeline: detection, retrieval and classification and computation and visualization.
Paul Resnick, Professor of Information, University of Michigan
Paul Resnick is the Michael D. Cohen Collegiate Professor of Information at the University of Michigan. He was a pioneer in the field of recommender systems (sometimes called collaborative filtering or social filtering). Recommender systems guide people to interesting materials based on recommendations from other people. The GroupLens system he helped develop was awarded the 2010 ACM Software Systems Award. His articles have appeared in Scientific American, Wired, Communications of the ACM, The American Economic Review, Management Science, and many other venues. His 2012 MIT Press book (co-authored with Robert Kraut), was titled “Building Successful Online Communities: Evidence-based Social Design”.