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The Structure of Information Pathways in a Social
Communication Network
Social networks are of interest to researchers in part because they
are thought to mediate the flow of information in communities and
organizations. Here we study the temporal dynamics of communication
using on-line data, including e-mail communication among
the faculty and staff of a large university over a two-year period.
We formulate a temporal notion of “distance” in the underlying
social network by measuring the minimum time required for information
to spread from one node to another — a concept that
draws on the notion of vector-clocks from the study of distributed
computing systems. We find that such temporal measures provide
structural insights that are not apparent from analyses of the pure
social network topology. In particular, we define the network backbone
to be the subgraph consisting of edges on which information
has the potential to flow the quickest. We find that the backbone is
a sparse graph with a concentration of both highly embedded edges
and long-range bridges—a finding that sheds new light on the relationship
between tie strength and connectivity in social networks.
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