Abstract - 
In this talk we present current and ongoing work about how humans create networks of information and how we can leverage some of those networks pursuit of knowledge. At a time when information seekers first turn to digital sources for news and information, it is critical that we understand the role that social media plays in the creation of digital artifacts. This is especially true when information consumers also act as information producers and editors through their online activity. In order to better understand the effects that editorial ratings have on online human behavior, we report the results of a two large-scale experiments in social media. Our second project uses many collectively annotated digital artifacts in order to understand their meaning. We do this through a fact checking exercise, where we test the veracity of factual declarations, represented as a subject, predicate and an object triple and where the subject and the object represent some real-world entity or idea and the predicate represents some one-way relationship between the subject and the object. Tasks like automated fact checking are easy when a true fact-triple is present in the knowledge graph; however, if a knowledge graph is a missing some fact it could be that (1) the statement is false or (2) the statement is true, but missing from the knowledge graph. To that end, we have created a ``definition machine'' that automatically infers an explanation-model that interprets the asserted predicate's definition with respect to the subject and the object and learns to deeply understand the meaning behind certain relationships.

Bio - 
Tim Weninger is an Assistant Professor at the University of Notre Dame where he directs the Data Science Group and is a member of the Interdisciplinary Center for Networks Science and Applications (ICENSA). His research interests are in data mining, machine learning and network science. The key application of his research is to identify how humans generate, curate and search for information in the pursuit of knowledge. He uses properties of these emergent networks to reason about the nature of relatedness, membership and other abstract and physical phenomena.