Stevens University Professor, Annenberg School for Communication, University of Pennsylvania
Duncan Watts is a pioneer in the use of data to study social networks. His research on social networks and collective dynamics has appeared in a wide range of journals, from Nature, Science, and Physical Review Letters to the American Journal of Sociology and Harvard Business Review. He is the author of three books: Six Degrees: The Science of a Connected Age (W.W. Norton 2003), Small Worlds: The Dynamics of Networks between Order and Randomness (Princeton University Press 1999), and Everything is Obvious: Once You Know the Answer (Crown Business 2011). He is the twenty-third Penn Integrates Knowledge University Professor at the University of Pennsylvania. In addition to his appointment at the Annenberg School, he holds faculty appointments in the Department of Computer and Information Science in the School of Engineering and Applied Science, and the Department of Operations, Information and Decisions in the Wharton School, where he is the inaugural Rowan Fellow. Before coming to Penn, Watts was a principal researcher at Microsoft Research (MSR) and an A. D. White Professor at Large at Cornell University. Prior to joining MSR in 2012, he was a professor of sociology at Columbia University, and then a principal research scientist at Yahoo! Research, where he directed the Human Social Dynamics group. He holds a BSc in physics from the Australian Defence Force Academy, from which he also received his officer’s commission in the Royal Australian Navy, and a PhD in theoretical and applied mechanics from Cornell University. asc.upenn.edu/people/faculty/duncan-watts-phd
Duncan is speaking at
Watch the prerecorded talks for this session beginning on Oct. 15. (Video embargoed until 4:00 p.m. ET 10/22/20.) Then tune in here on Oct. 22 for live Q&A with the speakers.
We in the mainstream media, stung by unfair tarring with the "fake news" label, are hypersensitive to the growth of actual misinformation online. And it's galling to see our Twitter feeds and the comment streams beneath our stories polluted by bigoted, chauvinistic, and sometimes threatening snark and vitriol. But new research suggests this front-row view to the downsides of free speech may have distorted our perspectives on these problems. Powerful observation biases skew what we as science writers see, compared to the general public.
In this session, researchers who have assembled big data sets to study these questions will present more objective views of the consumption of misinformation by the public and of how people respond to organized hate speech. The results of their quantitative analyses of large-scale, longitudinal studies challenge conventional wisdom about these phenomena.
Two scientists from the Santa Fe Institute who have used AI to classify nearly 200,000 Twitter conversations, spanning four years of activity on political accounts and large news sites in Germany, will share answers to a crucial question: is it better to ignore trolls or to combat them with counter-speech?
Then a data scientist at Penn who previously worked at Yahoo and Microsoft Research will update us on what his team's study of media consumption among large, nationally representative audiences in the U.S. reveals about how often Americans are exposed to truly fake news—and news of all kinds. The problems of ensuring an informed electorate, this research suggests, are quite different from what most of us have assumed.
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