CUPC Research Presentation: Brian C. Keegan

When: Thursday, October 26th 12:30 pm - 1:30 pm
Where: IBS 155B
Who: Dr. Brian C. Keegan, Assistant Professor, CU Boulder

A Sequence Analysis Agenda for Computational Social Science


Behavioral sequences are a fundamental but overlooked unit of analysis for understanding the structure and dynamics of social systems. Socio-technical systems like Wikipedia provide a rich dataset to understand the complex social behaviors generating reliable and popular knowledge artifacts. I share findings from two studies exploring how to apply sequence analysis methods to socio-technical system data. The first uses a data set of 37,515 revisions from 16,616 unique editors to 96 Wikipedia articles as a case study to understand the prevalence and significance of different sequences of editing patterns as general classes of behavioral motifs. The second study integrates sequence and network analysis methods to understand the roles and practices supporting high-tempo collaborations on Wikipedia following the 2011 Japanese earthquake, tsunami, and nuclear disasters. I outline a research agenda for computational social science researchers to understand the relationships, patterns, antecedents, and consequences of sequential behavior extending methods already developed in fields like sociology and bio-informatics.


About Professor Keegan:

Brian Keegan is an assistant professor in the Department of Information Science. He uses computational methods to analyze and theorize about how large-scale social systems respond under stress. This work is motivated the observation that social life rarely unfolds at a steady state; bursts, sequences, and other dynamics play crucial roles in structuring the social world around us. His previous research used digital trace data from large-scale socio-technical systems to understand the evolution of social structure in high-tempo online collaborations like Wikipedia’s rapid coverage of current events and more recent work explores the dynamics of collective computed-mediated attention to mass media events as well as cross-cultural team assembly processes in online games. He was previously a research associate in learning analytics at the Harvard Business School (2014–2016) and a post-doctoral research fellow in computational social science at Northeastern University (2012– 2014). He received his Ph.D. in Media, Technology, and Society from Northwestern University’s School of Communication in 2012 and S.B. degrees in Mechanical Engineering and Science, Technology, and Society from the Massachusetts Institute of Technology in 2006.