Talk Abstract: Science and Verifiability in Wikipedia. One of the key mechanisms that allows Wikipedia to maintain its high quality is the use of inline citations. Through citations, readers and editors make sure that information in an article accurately reflects its source. In this talk, we will see how we are using machine learning to discover whether—and why—any given sentence on Wikipedia may need a citation, in order to help editors identify areas of content violating the verifiability policy.
Bio: Miriam Redi is a Research Scientist at the Wikimedia Foundation and Visiting Research Fellow at King’s College London. Formerly, she worked as a Research Scientist at Yahoo Labs in Barcelona and Nokia Bell Labs in Cambridge. She received her PhD from EURECOM, Sophia Antipolis. She conducts research in social multimedia computing, working on fair, interpretable, multimodal machine learning solutions to improve knowledge equity.