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"Analyzing Organizational Routines in Online Knowledge Collaborations: A Case for Sequence Analysis in Computational Social Science"

Brian Keegan, a data scientist with the Harvard Business School's HBX online learning platform, presents a case study of sequence analysis of Wikipedia article edits.

May 12, 2016
from 12:00 PM to 01:00 PM


Research into socio-technical systems like Wikipedia has overlooked important structural patterns in the coordination of distributed work. This paper argues for a conceptual reorientation towards sequences as a fundamental unit of analysis for understanding work routines in online knowledge collaboration. We 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. Using a data set of 37,515 revisions from 16,616 unique editors to 96 Wikipedia articles as a case study, we analyze the prevalence and significance of different sequences of editing patterns. We illustrate the mixed method potential of sequence approaches by interpreting the frequent patterns as general classes of behavioral motifs. We conclude by discussing the methodological opportunities for using sequence analysis for expanding existing approaches to analyzing and theorizing about co-production routines in online knowledge collaboration.

About the speaker

Brian Keegan is currently a research associate at the Harvard Business School, where he works as a data scientist on the HBX online learning platform. He was previously a post-doctoral research fellow in computational social science with David Lazer at Northeastern University. His research there examined how social media like Twitter and Wikipedia can be used to improve predictive models of electoral success as well as performing small group experiments using the Volunteer Science platform. He defended his Ph.D. in the Media, Technology, and Society program at Northwestern University’s School of Communication in 2012. His dissertation examined the dynamic networks and novel roles which support Wikipedia’s rapid coverage of breaking news events like natural disasters, technological catastrophes, and political upheaval.
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