[Colloquium] TOMORROW | THURSDAY NOV 9 - DAMON CENTOLA at the Computational Social Science Workshop

Wed Nov 8 08:04:35 CST 2017

THE COMPUTATIONAL SOCIAL SCIENCE WORKSHOP PRESENTS
DAMON CENTOLA
ASSOCIATE PROFESSOR IN THE ANNENBERG SCHOOL FOR COMMUNICATION, DIRECTOR OF THE NETWORK DYNAMICS GROUP
UNIVERSITY OF PENNSYLVANIA

The Computational Social Science Workshop <https://macss.uchicago.edu/content/computation-workshop> at the University of Chicago cordially invites you to attend this week’s talk:

NETWORK DYNAMICS OF SOCIAL INFLUENCE IN THE WISDOM OF CROWDS<https://github.com/uchicago-computation-workshop/damon_centola/blob/master/2017__centola__wisdom_of_crowds.pdf>

THURSDAY, 11/09/2017
11:00AM-12:20PM
KENT 120

A light lunch will be provided by Pizza Capri.

Abstract: Since the discovery of the wisdom of crowds over 100 years ago theories of collective intelligence have held that group accuracy requires either statistical independence or informational diversity among individual beliefs. Empirical evidence suggests that allowing people to observe the beliefs of others leads to increased similarity of individual estimates, reducing independence and diversity without a corresponding increase in group accuracy. As a result, social influence is expected to undermine the wisdom of crowds. We present theoretical predictions and experimental findings demonstrating that, in decentralized networks, social influence generates learning dynamics that reliably improve the wisdom of crowds. We identify general conditions under which influence, not independence, produces the most accurate group judgments.

Damon Centola is an Associate Professor in the Annenberg School for Communication at the University of Pennsylvania, where he is Director of the Network Dynamics Group <http://ndg.asc.upenn.edu/> . Before coming to Penn, he was an Assistant Professor at M.I.T. and a Robert Wood Johnson Fellow at Harvard University. Centola completed his Ph.D. in sociology at Cornell University where he was an NSF IGERT Fellow in Non-linear Dynamics and Complex Systems. He is currently a Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford University.

Centola’s work addresses the theory of how behaviors spread through social networks. His research uses computational models and online experiments to study innovation diffusion, social epidemiology and cultural evolution. His papers have been published across several disciplines, including sociology, physics, and public health, appearing in journals such as Science, the Proceedings of the National Academies of Sciences, and the American Journal of Sociology. His work received the American Sociological Association’s Award for Outstanding Article in Mathematical Sociology in 2006, 2009, and 2011, and has garnered the ASA’s Goodman Award for Outstanding Contributions to Sociological Methodology. He has developed new computational and experimental technologies, including the NetLogo Agent Based Modeling environment, and was awarded a U.S. Patent for inventing a method for building online networks to promote diffusion. Recent popular accounts of Centola’s work have appeared in The New York Times, Wired, and CNN. His research has been funded by the Robert Wood Johnson Foundation, the National Science Foundation, the National Institutes of Health, the James S. McDonnell Foundation, and the Hewlett Foundation.

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The 2017-2018 Computational Social Science Workshop <https://macss.uchicago.edu/content/computation-workshop> meets each Thursday from 11 to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.

Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page <https://github.com/uchicago-computation-workshop/damon_centola/issues> of the workshop’s public repository on GitHub.<https://github.com/uchicago-computation-workshop/damon_centola> Further instructions are documented in the Computational Social Science Workshop’s README on Github.<https://github.com/uchicago-computation-workshop/README>
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