Title: A Team-Formation Algorithm for Faultline Minimization,
Abstract: In recent years, the proliferation of online resumes and the need to evaluate
large populations of candidates for on-site and virtual teams have led to a
growing interest in automated team-formation. Given a large pool of candidates,
the general problem requires the selection of a team of experts to complete a
given task. Surprisingly, while ongoing research has studied numerous
variations with different constraints, it has overlooked a factor with a
well-documented impact on team cohesion and performance: team faultlines.
Addressing this gap is challenging, as the available measures for faultlines in
existing teams cannot be efficiently applied to faultline optimization. In this
work, we meet this challenge with a new measure that can be efficiently used
for both faultline measurement and minimization. We then use the measure to
solve the problem of automatically partitioning a large population into
low-faultline teams. By introducing faultlines to the team-formation
literature, our work creates exciting opportunities for algorithmic work on
faultline optimization, as well as on work that combines and studies the
connection of faultlines with other influential team characteristics.