Events
Past Event
WED@NICO WEBINAR: Madeline King Kneeland, Cornell University "Agency and the Dynamics of Network Churn"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
Details
Speaker:
Madeline King Kneeland, Assistant Professor, SC Johnson College of Business, Cornell University
Title:
Agency and the Dynamics of Network Churn
Abstract:
Social networks are constantly evolving, however our understanding of how these changes influence performance outcomes is still limited. Importantly, network changes represent a combination of decisions the individual makes for her own network and decisions imposed by others. In order to understand the link between network churn, the aggregate change of added and dropped ties across time, and individual performance, we must consider agency in who initiates the network change. In two related projects, I theorize and empirically test the performance implications of these different dynamic changes and the role of agency (who initiates the change) within individuals’ networks in the context of a large, U.S. based law firm. Using 96 months of complete billable hour records for 759 partners, I show that churn initiated by the focal individual and churn that is imposed upon the individual are differentially productive in generating client revenue, particularly at high levels of churn. I establish that, beyond network structure, network dynamics play a powerful role in predicting professional success—although only after disentangling who initiates the decisions. To further explore how individuals create churn within their networks, I examine the opportunity shocks created by annual partner meetings to forge new ties within the organization and to become the target of tie formation from others.
Speaker Bio:
Madeline King Kneeland is an assistant professor of Strategy and a Management and Organization area faculty member in the Cornell SC Johnson College of Business. She earned a PhD in management from New York University’s Stern School of Business and a bachelor's degree in Psychology and Art History from Williams College. Professor Kneeland’s research spans strategy and organizational theory and answers questions related to social networks, network dynamics, and innovation. Another stream of her research explores how individuals and firms are able to create unusual and technologically distant innovation.
Webinar:
Webinar link: https://northwestern.zoom.us/j/96465098334
Passcode: nico
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between.
Time
Wednesday, November 4, 2020 at 12:00 PM - 1:00 PM
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Data Science Nights - MAY 2026 - Speaker: Xudong Tang, Computer Science and NICO
Northwestern Institute on Complex Systems (NICO)
5:30 PM
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M416, Technological Institute
Details
MAY MEETING: Thursday, May 28, 2026 at 5:30pm (US Central)
LOCATION:
ESAM Conference Room, Tech M416
2145 Sheridan Road, Evanston, IL 60208
AGENDA:
5:30pm - Meet and greet with refreshments
6:00pm - Talk with Xudong Tang, PhD Student, Computer Science, NICO, and the Human-AI Collaboration Lab, Northwestern University
TALK TITLE:
Human and Machine Perception of Voice Similarity
ABSTRACT:
Modern voice cloning systems generate synthetic speech that listeners frequently cannot identify as being synthetic. But a voice can sound natural without sounding like the intended person, and what determines whether a clone is heard as a particular person is an open question. Here we report a large-scale preregistered experiment in which we collected 92,239 responses from 175 participants on their perception of pairs of real recordings, voice clones, and continuously morphed voices drawn from 100 contemporary celebrities across 20 speaker groups. We find that voice clones do not reliably preserve perceived speaker identity, reducing same-speaker judgments by 12.7 percentage points even though the clones are produced by a state-of-the-art text-to-speech model, while leaving different-speaker judgments unchanged. Using continuously morphed stimuli, we find that speakers vary substantially in how much variation their perceived identity tolerates, and that this variation is not predicted by speaker demographics. Speaker embeddings account for 58.9\% (95\% CI = [55.7, 61.9]) of variance in identity judgments, which is more than acoustic features, social attributes, and clone status combined. Once all these observed features are accounted for, clone status adds no additional predictive power. These results shows that the perceptual impact of voice cloning is positional rather than categorical: we can model how listeners judge a voice by how close it falls to the perceptual boundary that defines each speaker's recognizable voice, applying the same criterion to real and synthetic speech alike.
DATA SCIENCE NIGHTS are monthly meetings featuring presentations and discussions about data-driven science and complex systems, organized by Northwestern University graduate students and scholars. Students and researchers of all levels are welcome! For more information: http://bit.ly/nico-dsn
FUTURE DATES:
Data Science Nights will return in September!
Time
Thursday, May 28, 2026 at 5:30 PM - 7:00 PM
Location
M416, Technological Institute Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Spring 2026 Commencement
University Academic Calendar
All Day
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Spring 2026 Commencement
Time
Sunday, June 14, 2026
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University Academic Calendar
Juneteenth - University Closed
University Academic Calendar
All Day
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Juneteenth - University Closed
Time
Friday, June 19, 2026
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University Academic Calendar
Independence Day (observed) - University Closed
University Academic Calendar
All Day
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Independence Day (observed) - University Closed
Time
Friday, July 3, 2026
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University Academic Calendar
Fall 2026 Classes Begin
University Academic Calendar
All Day
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Fall 2026 Classes Begin
Time
Wednesday, September 23, 2026
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University Academic Calendar