rewired—a strong possibility in GSJ
and the Dark Web. However, such rewiring would not affect Meth World
or the gang network because a co-occurrence link could not be rewired
once it was created.
An interesting topology-related
question is what mechanisms play a
role in producing the properties we
observed in dark networks? Short average path length, high clustering coefficient, power-law degree distributions with two-regime scaling behavior
in the human networks? That is, can
we regenerate the four dark networks
based on known mechanisms (such as
growth and preferential attachment)?
To answer, we conducted a series of
simulations in which we generated
30 networks for each elicited human
network based on three evolutionary
mechanisms:
Growth. Starting with a small number of nodes, at each time step we add
a new node to connect with existing
nodes in the network;
Preferential attachment. The probability that an existing node will receive
a link from the new node depends on
the number of links the node already
maintains. The more links it has the
more likely it will receive a new link;
and
New links among existing nodes. At
each time step, a random pair of existing nodes may connect, depending on
the number of common neighbors they
have. The more common neighbors
they share the more likely they will also
be connected with each other.
We expected that the first two
mechanisms would generate a power-law degree distribution1 and that the
third would generate a high clustering
coefficient and two-regime scaling behavior. 2 Our simulations showed that
the power -law degree distributions
are easily regenerated, with R2 ranging
from 0.83 (the gang network) to 0.88
(GSJ). The two-regime scaling behavior was also present in the simulated
networks for the human networks.
However, the highest clustering coefficient in a simulation was only 0.24
(GSJ), far less than what we obtained
from the elicited networks (0.55–0.68).
This finding implies that some other
mechanisms must have contributed
to the substantially high clustering
coefficients we observed in the dark
the terrorists in
the GsJ network
are on average
only 2. 5 links
away from bin
Laden himself,
meaning his
command
is able to reach
an arbitrary
member through
only two mediators.
networks. We suspect that member
recruitment is one such mechanism.
Employing active recruitment methods, subgroups of terrorists or criminals are able to attract new members
into their groups. The new members
quickly become acquainted with
many existing members, substantially
increasing the clustering coefficients.
caveats
A notable point is that two problems
may have affected the structures of the
three elicited human networks—GSJ,
Meth World, and the gang network.
First, they may have missing links that
can cause the networks to appear to
be less efficient; there may actually be
hidden “shortcuts” connecting distant parts of the networks. Second, the
presence of coincidental “fake” links
might cause the elicited networks
to be more efficient than they would
otherwise be since these links are not
communication channels.
To test how the results would be
affected by missing links, we added
various percentages of the existing
links to the elicited networks based
on three effects used in missing-link-prediction research: 7
Random effect. A link is added between a randomly selected pair of
nodes not originally connected;
Common neighbor effect. A link is
added between a pair of unconnected
nodes if they share common neighbors; the more common neighbors
they share the more likely they will be
connected; and
Preferential attachment effect. The
probability that a pair of unconnected
nodes will be linked together depends
on the product of their link degrees.
We found that the small-world and
scale-free properties of the four networks do not change when missing
links are added. For example, when
we added up to 10% of the links, the
average path lengths ranged from 3. 55
links (GSJ, preferential-attachment
links added) to 9. 45 links (the gang
network, common-neighbor links
added); the clustering coefficients
ranged from 0.45 (GSJ, random links
added) to 0.67 (the gang network,
common-neighbor links added); and
the R2 of power-law degree distributions ranged from 0.61 (GSJ, random
links added) to 0.93 (the gang network,