Fall classes begin 8 a.m.

Speaker:

Michael W. Macy - Goldwin Smith Professor of Arts and Sciences, and Director, Social Dynamics Laboratory, Cornell University.

Title:

Which Side Are You On: The Unpredictability of Partisan Alignments

Abstract:

TBA

Speaker Bio:

Michael Macy (B.A., Ph.D Harvard; M.A. Stanford) is Goldwin Smith Professor of Arts and Sciences at Cornell and Director of the Social Dynamics Lab, with a dual appointment in the Departments of Sociology and Information Science. With support from the U.S. National Science Foundation, Minerva Initiative, DARPA, and the National Research Foundation of Korea, his research team has used computational models, online laboratory experiments, and digital traces of device-mediated interaction to explore familiar but enigmatic social patterns, such as circadian rhythms, network topology and economic opportunity, lifestyle politics, the willingness to “pay it forward,” the mesh of civilizations, the spread of complex contagions, the polarization of opinion, segregation of neighborhoods, the emergence and collapse of fads, the spread of self-destructive behaviors, and the critical mass in collective action. His research has been published in leading journals, including Science, PNAS, Science Advances, Nature Human Behaviour, American Journal of Sociology, American Sociological Review, and Annual Review of Sociology.

Live Stream:

bluejeans.com/8474912527

Related Info

FALL KICKOFF MEETING: Wednesday, September 25, 2019 at 6:30pm in Chambers Hall, Evanston

DATA SCIENCE NIGHTS are monthly hack nights on popular data science topics, organized by Northwestern University graduate students and scholars. Aspiring, beginning, and advanced data scientists are welcome!

LECTURE: "Open standards for machine learning model deployment" with IBM Developer Advocate Svetlana Levitan.

This year, for the fall kickoff of Data Science Nights we are excited to host a representative of IBM Cognitive Applications for Chicago, Svetlana Levitan. Svetlana is a Developer Advocate of IBM with many years of experience with IBM statistical Software SPSS, and Predictive Model Markup Language (PMML). She is the Chicagoland Technical Experts Community Chairperson, a Meetup organizer for Big Data Developers, Open Source Analytics, and Chicago Cloud Developers, and is also part of the Center for Open-Source Data and AI Technologies (CODAIT). This is an excellent opportunity to connect with IBM representatives!

AGENDA:

6:15pm - Refreshments
6:30pm - Presentation by Svetlana Levitan, IBM Developer Advocate, IBM Cognitive Applications.
7pm - Discussion about topics and working groups for future hacking night sessions

For more info: data-science-nights.org

Supporting Groups:

This event is supported by the Northwestern Institute for Complex Systems and the Northwestern Data Science Initiative, in collaboration with ACiDS.

Related Info

Speaker:

Joshua Becker - Postdoctoral Fellow, Kellogg School of Management and NICO

Title:

Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion

Abstract:

Research on the “wisdom of crowds” has found that the average belief in a group can be remarkably accurate even when individual group members are wildly inaccurate. This phenomenon has been observed for domains ranging from financial forecasting to medical diagnoses, and a common theoretical claim is that group beliefs are most accurate when they are collected from individuals who are socially and statistically independent. However, the requirement for independence poses a challenge in many social and organizational settings where interaction and communication are an intrinsic part of decision-making. In contrast, I show that social information processing can produce beliefs that are even more accurate than the collected beliefs of independent individuals—under the right conditions. This talk will present formal models and behavioral laboratory experiments to identify when, and why, group interaction can help (or hurt) numeric belief accuracy. The main focus of this talk compares mediated information exchange (i.e., the “Delphi method”) with unstructured discussion, showing how network theory can resolve longstanding contradictions in previous research. All discussed data is available on GitHub and my website.

Working Paper: https://bit.ly/2lZ6zHF

Speaker Bio:

Joshua Becker is a postdoctoral fellow at Kellogg School of Management and a researcher-in-residence at NICO. Joshua completed his PhD at the Annenberg School for Communication, University of Pennsylvania, with a focus on the network dynamics of collective intelligence. Their research has been published in venues including Science, Proceedings of the National Academy of Sciences, and Harvard Business Review. Prior to grad school Joshua worked professionally in conflict mediation (now serving pro bono) an experience that inspires their research on communication and decision-making.

Live Stream:

bluejeans.com/8474912527

Related Info

Speaker:

TBA

Title:

TBA

Abstract:

TBA

Speaker Bio:

TBA

Live Stream:

bluejeans.com/8474912527

Related Info

Speaker:

TBA

Title:

TBA

Abstract:

TBA

Speaker Bio:

TBA

Live Stream:

bluejeans.com/8474912527

Related Info

Speaker:

TBA

Title:

TBA

Abstract:

TBA

Speaker Bio:

TBA

Live Stream:

bluejeans.com/8474912527

Related Info

Speaker:

TBA

Title:

TBA

Abstract:

TBA

Speaker Bio:

TBA

Live Stream:

bluejeans.com/8474912527

Related Info

Speaker:

TBA

Title:

TBA

Abstract:

TBA

Speaker Bio:

TBA

Live Stream:

bluejeans.com/8474912527

Related Info

Speaker:

TBA

Title:

TBA

Abstract:

TBA

Speaker Bio:

TBA

Live Stream:

bluejeans.com/8474912527

Related Info