Databases Reference
In-Depth Information
What's interesting about this local bridge is that it describes a communication channel
between groups in our organization. Such channels are extremely important to the
vitality of our enterprise. In particular, to ensure the health of our company we'd make
sure that local bridge relationships are healthy and active, or equally we might keep an
eye on local bridges to ensure no impropriety (embezzlement, fraud, etc.) occurs.
Finding Your Next Job
This notion of weak social links is particularly pertinent in algorithms like (social) job
search. The remarkable thing about job searches is that it's rarely a close friend that
provides the best recommendation, but a looser acquaintance.
Why should this be? Our close friends share a similar world view (they're in the same
graph component
) and have similar access to the available jobs data and hold similar
opinions about those jobs. A friend across a local bridge is clearly in a different social
network (a different component), with correspondingly different access to jobs and a
different viewpoint about them. So if you're going to find a job, look across a local bridge
because that's where people who have different knowledge to you and your friends hang
out.
This same property of local bridges being weak links (
PEER_OF
in our example organi‐
zation) is a property that is prevalent throughout social graphs. This means we can start
to make predictive analyses of how our organization will evolve based on empirically
derived local bridge and strong triadic closure notions. So given an arbitrary organi‐
zational graph, we can see how the business structure is likely to evolve and plan for
those eventualities.
Summary
Graphs are truly remarkable structures. Our understanding of them is rooted in several
hundred years of mathematical and scientific study. And yet we're only just beginning
to understand how to apply them to our personal, social, and business lives. The tech‐
nology is here, open and available to all in the form of the modern graph database; the
opportunities are endless.
As we've seen throughout this topic, graph theory algorithms and analytical techniques
are not demanding: we need only understand how to
apply
them to achieve our goals.
We leave this topic with a simple call to arms: embrace graphs and graph databases; take
all that you've learned about modeling with graphs, graph database architecture, de‐
signing and implementing a graph database solution, and applying graph algorithms to
complex business problems, and go build the next truly pioneering information system.
