Presentation
Unraveling Team Dynamics: Decomposing Multilayer Networks for Insights into Joint Performance
DescriptionDespite consistent progress in the science of teaming that spans decades, there remains a gap in the literature concerning longitudinal teaming research. Some longitudinal research has shown that teams change the types and quantities of interactions and communications they require as they gain experience. Importantly, these different types of interactions entail changing interdependencies in the team’s multimodal relations. One possible way to represent these changing team dynamics is as a complex multivariate network with a non-stationary topology. Considering this, the primary objective of our study is to determine if topological configurations of a complex network representation of team interactions map onto specific phases of team maturation and development. In our findings, we demonstrate the efficacy of multiplex recurrence networks combined with tensorial decomposition for analyzing the dynamics of multi-modal teaming data to identify how complex patterns of team interactions change over time.
Contributor
Core Research Area Lead
Event Type
Lecture
TimeWednesday, September 11th1:50pm - 2:10pm MST
LocationFLW Salon J
Human Performance Modeling