Pattern Anarchy: Toward a Libertarian Understanding of Network
Theory
Compiled by Michael McCarron
Patterns
in society are easy to see. We recognize them everyday whether it is the same
people at the bus stop at the same time on your morning commute or the same
people dominating meetings we know that humans act in identifiable ways.
However, the study of these patterns and emergent behaviors is a relatively
modern phenomenon. Social Network and Network Theory Analysis are some of the
latest sciences to attempt at understanding behavior in networks from social
networks to biological networks we can see defined patterns and emergent
behavior. This is a brief overview of Network Theory with brief remarks on how
it is relevant to Libertarian Socialist organizing. SOME KEY CONCEPTS IN NETWORK
THEORY"Network theory or diktyology is a subject within applied mathematics and
physics, and coincides with graph theory. It has application in a varied range
of disciplines including computer science, biology, economics, and sociology.
Network theory concerns itself with the study of graphs as a representation of
either symmetric relations or, more generally, of asymmetric relations between
discrete objects. Typically, the graphs of concern in network theory are complex
networks, examples of which include the World Wide Web, the Internet, gene
regulatory networks, metabolic networks, social networks, epistemological
networks, etc."
http://en.wikipedia.org/wiki/Network_theory Networks display certain emergent behaviors, that is to say they exhibit
self-organization without any central planning authority. There are several
types of networks however for our purposes we are concerned with what have
become known as "scale-free networks" which is a complex network:
"Most social, biological, and technological networks (as well as
certain network-driven phenomena) can be considered complex by virtue of
non-trivial topological structure (see e.g., social network, computer network,
neural network, epidemiology). Such non-trivial features include: a heavy-tail
in the degree distribution; a high clustering coefficient; assortativity or
disassortativity among vertices; community structure at many scales; and
evidence of a hierarchical structure." http://en.wikipedia.org/wiki/Complex_network
A scale
free network is defined as:"In scale-free networks, some nodes act as "highly
connected hubs" (high degree), although most nodes are of low degree. Scale-free
networks' structure and dynamics are independent of the system's size N, the
number of nodes the system has. In other words, a network that is scale-free
will have the same properties no matter what the number of its nodes is. Their
most distinguishing characteristic is that their degree distribution follows a
power law relationship" http://en.wikipedia.org/wiki/Scale-free_networks
As
left libertarians we may automatically see some interesting similiarities to how
we organize, we often group ourselves into hubs that can act as conduits to
integrating more nodes or people into our networks, there is no central planning
authority and links are made freely between different nodes in the networks but
hubs do remain. These hub clusters which we may even see as embodiments of the
protest clusters of affinity groups shape the overall network topology of
libertarian activists. Some hubs have a high degree of what is known as
"preferential attachment":
"In preferential attachment, new nodes are added to the network one
by one. Each new node attaches itself (creates a link) to one of the existing
nodes with a certain probability. This probability is biased, however, in the
sense that it is proportional to the number of links that the existing node
already has. Therefore, heavily linked nodes ("hubs") tend to quickly accumulate
even more links, while nodes with only a few links are unlikely to be chosen as
the destination for a new link. It is as if the new nodes have a "preference" to
attach themselves to the already heavily linked nodes…. Preferential attachment
is an example of a positive feedback cycle where initially random variations
(one node initially having more links or having started accumulating links
earlier than another) are automatically reinforced, thus greatly magnifying
differences. This is also sometimes called the Matthew effect, "the rich get
richer", and in chemistry autocatalysis." http://en.wikipedia.org/wiki/Preferential_attachment
The notion of preferential attachment can be seen in how we
prioritize some peoples opinions over others it can also be seen in the
financial networks or markets as the rich-get-richer. The question of
preferential attachment in networks is a very interesting question to address as
libertarians for we seek an equitable distribution to the scale free network
flows. One issue that has been studied is the issue of "fitness" in terms of
preferential attachment:"The introduction of fitness does not eliminate growth
and preferential attachment, the two basic mechanisms governing network
evolution. It changes, however, what is considered attractive in a competitive
environment. In the scale-free model, we assumed that a node’s attractiveness
was determined solely by its number of links. In a competitive environment,
fitness also plays a role: Nodes with higher fitness are linked to more
frequently. A simple way to incorporate fitness into the scale-free model is to
assume that preferential attachment is driven by the product of the node’s
fitness and the number of links it has. Each new node decides where to link by
comparing the fitness connectivity product of all available nodes and linking
with a higher probability to those that have a higher product and therefore are
more attractive. Between two nodes with the same number of links, the fitter one
acquires links more quickly. If two nodes have the same fitness, however the
older one still has an advantage." Pg. 96, "Linked: How Everything is Connected
to Everything Else and What It Means for Business, Science and Everyday Life" by
Albert-Laszlo BarabasiWe can see that through fitness there is the possibility
of reducing the differential equation (extremes) between rich and poor nodes,
and thus help nodes to compete for links, money and other objects within the
network. This is one area of study that should be looked into further. How can
promoting fitness within a decentralized network help create equity among all
members of the network? One researcher, Valdis Krebs, has addressed the nature
of power in networks, while others have studied the economic impact of
preferential attachment in monetary networks such as the capitalist society we
live in:
"in markets the standard strategy is to drive the hardest possible
bargain on the immediate exchange. In networks, the preferred option is often
creating indebtedness and reliance [cooperation] over the long haul." Walter W.
Powell "Neither Market nor Hierarchy: Network Forms of Organization" http://www.cooperationcommons.com/Documents/EntryView?id=18
The
traditional tree-shaped corporate structure, suited to mass production, is
poorly suited to deal with rapid innovation and market change. The challenge of
competing in such environments led to industries like pharmaceuticals and
technology developing scale-free networks of alliances and outsourcers. For
years, economists spoke of a standard formal model of economics, in which
companies interact not with each other but with "the market," a theoretical
entity mediating economic transactions. Barabasi: "In reality, the market is
nothing but a directed network. The weight of the links captures the value of
the transaction, and the direction points from the provider to the receiver. The
structure and evolution of this weighted and directed network determine the
outcome of all macro economic processes." Id. pp.
208-209.
see,
http://www.visualcomplexity.com/vc/project_details.cfm?id=22&index=2&domain=Business%20Networksfor
a study on the ruling class’ social network. Dr. Krebs work shows us how power
in networks is created and how it can be deconstructed into more horizontal
forms of power law distributions:
"Two social network measures, Betweennness and Closeness, are
particularly revealing of a node’s advantageous or constrained location in a
network. The values of both metrics are dependent upon the pattern of
connections that a node is embedded in. Betweenness measures the control a mode
has over what flows in the network—how often is this node on the path between
other nodes? Closeness measures how easily a node can access what is available
via the network—how quickly can this node reach all others in the network? A
combination where a node has easy access to others, while controlling the access
of other nodes in the network, reveals high informal power." http://orgnet.com/PowerInNetworks.pdfHe
demonstrates how informal power is actually real power. Say we have a typical
hierarchical structure of a leader with followers. Yet the leader does not know
all the nodes or followers but some followers do know all the other followers.
Real power resides with the followers that know all the other followers. So the
power dynamic actually resides with the most linked node which has high
preferential attachment with other nodes in the network. Other studies have
found that preferential attachment is also a measure of class stratification an
early study, "Contacts and Influence" by Ithiel de Sola Pool (MIT) and Manfred
Kochen (U. of Michigan) Social Networks, 1 (1978/79) pg. 5-51
"Thus in a a country the size of the United States, if
acquaintanceship were random and the mean acquaintance volume were 1000, the
mean length of minimum chain between pairs of person would be well under two
intermediaries. How much longer it is in reality because of the presence of
considerable social structure in the society we do not know (nor is it
necessarily longer for all social structures). Those are among the critical
problems that remain unresolved. (emphasis added)" pg. 15"Increased social
stratification reduces the length of chains between person in the same stratum
and at the same time lengthens the chains across strata lines." Pg. 17"Blue
collar workers and housewives had the smallest number of different contacts over
the 100 days. They both lived in a restricted social universe." Pg. 23"The
tendency of society to cluster itself as like seeks like can also be seen in
Tables on contacts by age, sex and religion. These data reflect a society that
is very structured indeed." Pg. 23
Stuctures meant by the author are
analogous to any subdivision in a social network although here it is class
structure which impedes equitable linkage between different members of the
network. Yet, these structures are aptly referred to as modules in networks,
research has shown that networks are actually modular in structure and have many
different communities or modules in the overall architecture, some hubs may be a
community onto themselves or a hub may be a member of hub with other hubs of
communities. There are many suggested algorithms for understanding community
structure in networks. This understanding has led to the term of Modular
Scale-Free Networks:
"The hierarchical modularity of the protein interaction network
offered another biological example, reinterpreting the role of the hub proteins
as the mediators of different functional modules. Therefore, hierarchical
modularity is a generic property of most real networks, accompanying the
scale-free architecture." Pg. 237 Barabasi, "Linked"
However, one
should not read to much into the terminology of "hierarchical" for it is used in
many clustering activities at major protests that libertarians attend as well as
a structure that proved useful during the Spanish Civil War. In the same sense a
cluster is composed of different work groups or affinity groups is the same
sense as "Hierarchical" in this terminology of network theory. A graphical
reference shows how the structures interfere with equitable distribution, the
first being what a libertarian socialists ideal would be of a social network and
inter-linking relationship:
A second grouping with some interaction between different
groups, which would be a Liberal view, capitalism perhaps:
and finally one with complete social stratification with
structures divided between two groups, feudalism perhaps:
As one can see there are immediate points of recognition to
social network analysis and the critique made by libertarian socialists. We can
see how on one hand we live in scale free networks yet we can also see that
there is much to be done to improve fitness among the different nodes in the
real networks we live in. Structures, Communities, Modules and Factions lead to
extending networks distancing different nodes in the network from each other,
whether it is financial networks divided between the rich and the poor or a
network of activists that can’t get consensus to work well enough or open enough
to make the links between members short and direct thus increasing trust in the
group. When it comes to political organizing different authors have shown how
social networks are the prime force in political decision making. One study at
the grass roots level has found that networks of friends is a good way of
mobilizing support while not activating undo attention from
adversaries.Demographics is the wrong focus in political campaigns friendship
networks are far more valuable.
"To put this all another way, with the web system facilitating a
friend to friend campaign, we were able to recruit and utilize 2% of the
vote-eligible population as volunteers, and with that 2%, come very close to
saturating the potentially supportive population (late-comers to the volunteer
ranks complained that almost every person they could think of was taken),
without wasted effort and alienation or mobilization of the opposition."
"Targeting [demography] made little difference in the rate of success in
identifying supporters…""By utilizing the existing network of relationships
within a community, a friend to friend campaign is a community effort that
strengthens the social fabric. It also inspires the population to become a
community of activists, rather than a passive "market". "Friend to Friend
Politics and the "inside-out" campaign: a tale of three campaigns" By Pat
Dunlavey
Dr. Krebs has also studied social interaction and politics.
He has found that again socialization is of far more value then trying to target
certain demographics. For instance his study, "It’s the Conversations, Stupid!:
The link between social interaction and political choice" (
http://www.extremedemocracy.com/chapters/Chapter%20Nine-Krebs.pdf)
"… social voter—modern citizens do not make decisions in a social
vacuum. Who we know influences what we know and how we feel about it. After
controlling for personal attitudes and demographic membership, researchers found
social networks, that voters are embedded in, exert powerful influences on their
voting behavior. ""Research on voter participation in elections has revealed the
importance of social networks. Voter turnout is highly correlated among family,
friends and co-workers. If those in your social network vote, and make that
known, then there is a much higher probability that you will vote also. We are
all influenced by those who we view as similar to us. We may adopt the actions
of a similar others either through conformity or competition. To fit in with a
group, we conform to the actions of others. To keep up with those we view as
competitors, we mimic their behavior so as not be left behind.""Recent research
in social networks has shown that human networks tend to follow the small-world
model. The way people connect results in clusters according to common interests,
views, goals or affiliations—small worlds of people with similar sentiments.
Yet, clusters are not isolated from each one another. They are connected to each
other by bridging ties—Person X in Group A works with Person Y in Group B. Some
of these bridges are cross-cutting ties, or shortcuts, that minimize the
distance between all clusters. Shortcuts between otherwise distant cluster are
what make the world seems small—strangers in the mirror are closer then they
appear to be."
How can we make organizing more effective through
Network Theory? I’ll leave that up to each of us to address on our own.However,
one final thought is that of how networks do create their "intelligence
networks". Thus a "Collective Intelligence":Collective intelligence is an
amplification of the precepts of the Founding Fathers, as represented by Thomas
Jefferson in his statement, " A Nation’s best defense is an educated citizenry."
During the industrial era, schools and corporations took a turn toward
separating elites from the people they expected to follow them, Both government
and private sector organizations glorified bureaucracy and, with bureaucracy,
secrecy and compartmentalized knowledge. In the past twenty years, a body of
knowledge has emerged which demonstrates that secrecy is actually pathological,
enables selfish decisions against the public interest. Collective intelligence
restores the power of the people over their society, and neutralizes the power
of vested interests that manipulate information to concentrate wealth."If we
recognize that people exist in networks, which is hard to argue against, then we
must understand the role of a free thinking collective intelligence that is a
composite of the nodes that make up our networks. If we can learn to effectively
and equitably inter-network with the different nodes then we will decrease the
length between the different nodes thus increase harmony in our communities. We
can do this through harnessing, like the precepts of our radical direct
democracy, thoughts and feelings and understandings of all the members of our
networks. If you care to comment on this article you can contact me via
http://www.myspace.com/autonomous019 I am working on the next paper which shows how collaborative filtering could be
used as a means of adjusting preferential attachment, oh joy! Some academic
network theory articles, http://netwiki.amath.unc.edu/p.s. mind your security
culture ;-)
