When: November 11, 2022 12pm EST
Where: Remote Talk
Speaker: Jonas Juul
Title: Harder, better, faster, stronger cascades — or simply larger?
Do some types of online content spread faster or further than others? In recent years, many studies have sought answers to such questions by comparing statistical properties of network paths taken by different kinds of content diffusing online. Here we demonstrate the importance of controlling for correlations in the statistical properties being compared. In particular, we show that previously reported structural differences between diffusion paths of false and true news on Twitter disappear when comparing only cascades of the same size; differences between diffusion paths of images, videos, news, and petitions persist. Paired with a theoretical analysis of diffusion processes, our results suggest that in order to limit the spread of false news it is enough to focus on reducing the mean “infectiousness” of the information.
Joint work with Johan Ugander (Stanford University)
Jonas L. Juul is a Carlsberg Fellow postdoc at the Technical University of Denmark. His research focuses on spreading processes and networks. His recent interests include developing methods to infer how content spreads online from observed diffusion paths, and evaluating the efficiency of mitigation measures in epidemiology. Before joining the Technical University of Denmark he was a post-doctoral researcher at the Center for Applied Mathematics, Cornell University where he worked with Austin Benson, Jon Kleinberg and Steven Strogatz. He obtained his Ph.D. in Physics of Complex Systems from the Niels Bohr Institute in 2020.