Speaker:

Patrick Park, Assistant Professor, School of Computer Science, Carnegie Mellon University

Title:

Back to ‘Data’ Science in the Age of AI

Abstract:

Unconventional uses of data can stimulate creativity and innovation at scales that dwarf the creativity and innovation unlocked by unconventional applications of established knowledge. In this talk, I will present three studies, each motivated by separate questions of human behavior in social networks, yet collectively shed light on the benefits and challenges of unconventional uses of data. Using Twitter communication and tweet deletion data, the first study develops and tests a novel network mechanism through which network brokers’ individual decisions to self-censor can collectively lead to online opinion polarization. The second study applies sociological theory of interaction rituals to operationalize higher-order group interactions in a simplicial complex representation of communication among Twitter users. Analysis reveals that users who interact in a shared context tend to exhibit ritualistic aspects of offline group interaction, such as markedly higher communication frequency, focus on the collective, and stronger affect, which would not have been discernible in conventional graph-based representations. The final study attempts to explain the puzzle of scientific disruption, disproportionately produced by small teams in the age of big science. Analysis of scholarly acknowledgements in sociology journal publications suggests that small teams, perhaps by necessity, may produce disruptive knowledge in the course of seeking intellectual resources from informal academic ties positioned in distant niches in knowledge space. The talk will briefly reflect on the challenges of repurposing and/or combining data in unconventional ways, including construct validity, generalizability, survivorship bias, and research ethics, then conclude with potential implications for AI research.

Speaker Bio:

Patrick Park is a computational social scientist with research interests in the structure and evolution of large-scale social networks. His research focuses on how people form and maintain social ties at decade-long time scales and how the broader social, technological environment shape this process. Using population-scale online interaction data and computational models, his research addresses questions on the formation of rarely observed socially distant ties, social contagion, opinion dynamics, and signatures of higher-order group interactions that transcend dyadic representations of groups and appeared in interdisciplinary venues including Science, Social Networks, PLoS One, Lecture Notes in Computer Science, and Big Data and Society. He is currently assistant professor in the Software and Societal Systems Department (S3D) at Carnegie Mellon University School of Computer Science. Before joining CMU, He was postdoctoral fellow at the University of Michigan and Northwestern University after receiving his doctoral degree in sociology at Cornell University.

Location:

In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/95844553871
Passcode: NICO25

About the Speaker Series:

Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems, data science and network 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. Please visit: https://bit.ly/WedatNICO for information on future speakers.

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