We show how a wearable computing research plat-
form for measuring and analyzing human behavior
can be used to understand social systems. Using
a wearable sociometric badge capable of automati-
cally measuring the amount of face-to-face interac-
tion, physical proximity to other people, and relative
location, we are able to construct a dynamic view of
an organization’s social network by viewing interac-
tions as links between actors. Combining this with e-
mail data, where e-mail exchanges indicate a social
tie, we are able to form a robust view of the social net-
work, using proximity information to remove spurious
e-mail exchanges. We attempt to use on-body sensors
in large groups of people for extended periods of time
in naturalistic settings for the purpose of identifying,
measuring, and quantifying social interactions, infor-
mation flow, and organizational dynamics. We discuss
how this system can lead to an automatic intervention
system that could optimize the social network in real
time by facilitating the addition and removal of links
based on objective metrics in a socially natural way.
We deployed this research platform in a group of 22
employees working in a real organization over a pe-
riod of one month, and we found that betweenness in
the combined social network had a high negative cor-
relation of...