  This paper presents findings from a study of the email network of a large
scientific research organization, focusing on methods for visualizing and
modeling organizational hierarchies within large, complex network datasets. In
the first part of the paper, we find that visualization and interpretation of
complex organizational network data is facilitated by integration of network
data with information on formal organizational divisions and levels. By
aggregating and visualizing email traffic between organizational units at
various levels, we derive several insights into how large subdivisions of the
organization interact with each other and with outside organizations. Our
analysis shows that line and program management interactions in this
organization systematically deviate from the idealized pattern of interaction
prescribed by "matrix management." In the second part of the paper, we propose
a power law model for predicting degree distribution of organizational email
traffic based on hierarchical relationships between managers and employees.
This model considers the influence of global email announcements sent from
managers to all employees under their supervision, and the role support staff
play in generating email traffic, acting as agents for managers. We also
analyze patterns in email traffic volume over the course of a work week.
