Рет қаралды 169
Misinformation as a complex system
Presented by Michael Simeone
Misinformation is not a disease, yet we can't stop referring to it as such. In this presentation, we'll look at data from a handful of misinformation events as we try to undo one of the most durable conceptual frames used for understanding misleading content and inauthentic behavior: epidemiology. We'll discuss why tools from complex adaptive systems can help us better understand the present and past events as we prepare for future incidents and trends.
Michael Simeone is a researcher interested in multidisciplinary data science. He currently serves as the director of Data Science and Analytics for ASU Libraries at Arizona State University. He was the founding director of the Nexus Lab for Transdisciplinary Informatics at ASU from 2013-2016. He is also affiliated with the Chainbuilder decision support systems group, as well as the Innovative Software and Data Analysis Division at the National Center for Supercomputing Applications. His research includes multidisciplinary data science, post-cybernetic culture and technology, analysis of human-technology networks, data visualization, and data-driven collaborations that bridge environmental sciences and humanities. Currently, he serves as a Domain Champion for Humanities for the Extreme Science and Engineering Discovery Environment. He received his doctorate in English from the University of Illinois at Urbana-Champaign.