Team Science


Team Science aims to gain understanding of collaboration and innovation mechanisms through the lens of dynamic social network analysis.  We will observe the evolution of the C3N Project with surveys, interviews, group learning sessions, and ethnographic methods both conventional and digitally-enabled.  Team Science conducts network analyses by mining electronic communication (email) data to compare changes in social network structure and communication content with team and project-based outcomes.  We also assess "honest signals" of communication, such as the frequency of shifts in team leadership or individual speed of response to emails.  The primary research questions that motivate Team Science include:

  1. What patterns of interaction and communication predict high-performing innovation teams?
  2. How can the virtual mirroring of interaction and communication patterns enhance performance at the individual, team and network levels?
  3. How can the processes around virtual mirroring help us to design and manage emergent networked systems such as the C3N?

Answer to these questions will help us to gain novel insights in the drivers of collaborative innovation.  And on the practical side, we hope to improve creativity and performance across the C3N Project system.