Home / Lectures / Brian Keegan, Northeastern University
Narrating with Networks: Making Sense of Event Log Data with Socio-Technical Trajectories

Brian Keegan, Northeastern University
Description
Semester:
- Fall 2014
Speakers:
Lecture Time:
Fri, September 12, 2014 @ 1:30 pm to 3:00 pm
Lecture Location:
Room R1240, Ross School of Business
Speaker Webpage(s):
Introduced By:
Introduction by Management & Organizations PhD student Teddy DeWitt
Abstract
Network science provides a rich set of theories and methods to understand the structure and dynamics of complex social, information, and biological systems. These approaches traditionally demand data with explicitly declared dyadic relationships or interactions such as friendship or affiliation. However, socio-technical systems like Wikipedia, Github, or Twitter often encode latent relationships within event logs and other databases. Temporal adjacencies in these event logs reveal sequences of actions that have complex and non-random properties that illuminate hidden structures within peer production systems. Using several case studies, I describe how complex networks called “socio-technical trajectories” can be extracted from event logs to understand the behavior of both users and artifacts within these systems. These trajectories encode a variety of rich structural and dynamic data distinct from traditional network approaches and illustrate user social roles within distributed collaboration as well as context and shifting interests of users based on their contributions. This approach has rich implications for mixed-methods research as it allows researchers to collapse large-scale event log data into more parsimonious network representations that can motivate qualitative analysis, visualization, and statistical modeling of complex behavior in socio-technical systems.
Recording & Additional Notes
No additional notes available.