ity. The opposite pattern (
dissortativity) of well-connected nodes preferentially connecting to poorly connected
nodes and vice versa has been found
in a number of ecological, biological,
and technological networks. In other
words, while assortativity is observed
in networks characterized by sociality and collaboration, dissortative patterns appear to emerge in networks
evolving in a context that demands
resilience under selection pressures. It
may be easier to attack a system where
all the well-connected nodes are connected to each other than a system
where well-connected nodes are insulated from each other through poorly-connected nodes.
The concepts of assortativity and
dissortativity also highlight a tension
that exists in clandestine networks
like gold farming trade networks [ 7]:
should collaboration and efficiency be
prized despite the heightened risks of
detection or should resilience trump
efficiency and flexibility? Our analysis
(see Figure 2) demonstrates a very notable distinction. Affiliates and non-affiliates nodes clearly have assortative
mixing patterns in which characters
with many trading partners have a
tendency for their neighbors to also
be well-connected. However, the identified farmers exhibit a clear dissortative pattern. The CAVIAR network also
exhibits a strong dissortative pattern
and provides evidence of the mapping
of online behaviors back to offline behavior; clandestine networks in both
online and offline trafficking contexts
preferred to insulate well-connected
individuals from each other. Furthermore, a number of individual affiliate
accounts are well outside of the typical
range and are approximated much better by the gold farmer trend line. This
suggests assortativity metrics may be
useful for identification or prediction
of not only gold farmers, but other well-connected members of clandestine organizations.
WHAT THIS MEANS FOR
CRIMINAL AC TIVIT Y IRL
As MMOGs grow in scale and complexity, these exciting worlds and the
novel player interactions within them
assume increasing social relevance. In
provide a window
offline behavior that
is otherwise difficult
or impossible to
particular, gold farming offers a case
in which people are willing to pay a
premium to enhance their experience
in their leisure activities. However, the
production of virtual wealth outside of
community norms and rules offers a
striking example of how illicit goods,
clandestine organizations, and law
enforcement demands and limitations
also impinge on these game worlds.
Given these parallels, MMOGs potentially provide a window into understanding of offline behavior that is otherwise difficult or impossible to study.
Obviously the notion of markets,
property, and regulation within
MMOGs raise a variety of complicated
questions. What rights, if any, do players have over the digital artifacts they
create and develop? What are the offline social, cultural, and technological contexts in which virtual economic
production occurs? How should communities in online worlds respond to
potentially exploitative phenomenon
like inflation, arbitrage, and monopolies? How aggressively should administrators pursue deviants and traffickers
to balance community stability with
Very similar questions have preoc-
cupied social scientists, philosophers,
and political leaders since well before
the advent of the Internet. Indeed, it is
reassuring that despite how digitized
and distributed these virtual worlds
may be, MMOGs are still very human
systems that evince the same struggles
and debates that have preoccupied so-
cieties for ages. While the consequenc-
es of players’ trials and tribulations
within MMOGs may not directly affect
the “real world,” these online worlds
are still very real sites for social inter-
action, organization, and economic
trade. In that respect, MMOGs provide
truly exciting platforms to both under-
stand how human behavior unfolds
using immaculately documented data
as well as how to design technology to
support and enhance social and eco-
nomic interactions for both the online
and offline world.
Brian Keegan is a Ph. D. student at North western
University’s School of Communication. He studies team
assembly mechanisms under boundary conditions of online
Muhammad Aurangzeb Ahmad is a Ph. D. student in
Computer Science and Engineering at the University of
Minnesota. He studies computational trust in virtual worlds
and online reputation systems.
Dmitri Williams is an associate professor at the USC
Annenberg School for Communication. He studies the social
practices and implications of online communities and video
Jaideep Srivastava is a professor in computer science and
Engineering at the University of Minnesota. He uses web
mining to study online databases and multimedia systems
to model human interactions.
Noshir Contractor is the Jane & William White Professor of
Behavioral Sciences at Northwestern University. He studies
the factors that lead to the formation, maintenance, and
dissolution of dynamically linked social and knowledge
networks in communities.
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