Reading
Barabasi, A-L, and Bonabeau, E (2003), Scale-Free Networks. Scientific American, May 2003
Benkler (2006), chapter 7
Terranova (2004), chapter 2
http://www.barabasilab.com/index.php
Learning outcomes
To understand the non-random characteristics of complex networks
To apply theoretical models to the www and to social networks
To consider implications for public relations
Barabasi and Albert (1999)The probability that any node on the network will be very highly connected to many others is VERY LOW
The probability that a very large number of nodes will be connected very loosely or not at all is VERY HIGH
Preferential attachment: new nodes prefer to attach to well-attached nodes
Huberman and Adamic (1999)
Each website has an intrinsically different growth rate
New sites are formed at an exponential rate
PREFERENTIAL ATTACHMENT + GROWTH = ?
black: opinion leadersred: influenced green: uninfluenced grey: undecided
Viral marketing
http://www.orgnet.com
Hubs:
‘broadcast’ weakly infectious viruses,
ideas
ImplicationsThe more popular you are, the more popular you become
Niches are important
Older nodes (sites) tend to be more popular than new ones, but only on average
Money alone is not enough to guarantee future popularity or growth, but relevance and connection to already popular nodes can be
Clustering
Sites cluster into densely-linked regions or communities of interest
They link much more to each other than to nodes outside
Clustering increases and intensifies as you move along the “long tail”
28%: heavily 28%: heavily interlinked: interlinked:
multiple multiple redundant redundant
pathspaths
28%: heavily 28%: heavily interlinked: interlinked:
multiple multiple redundant redundant
pathspaths
22%: link to 22%: link to core, but not core, but not
from core; new, from core; new, or lower-or lower-
interest sitesinterest sites
22%: link to 22%: link to core, but not core, but not
from core; new, from core; new, or lower-or lower-
interest sitesinterest sites 22%: link from 22%: link from core, but not to core, but not to
core; doc core; doc depositories or depositories or
internal org internal org sitessites
22%: link from 22%: link from core, but not to core, but not to
core; doc core; doc depositories or depositories or
internal org internal org sitessites
22%: cannot 22%: cannot reach or be reach or be
reached from reached from corecore
22%: cannot 22%: cannot reach or be reach or be
reached from reached from corecore
10%: entirely 10%: entirely isolatedisolated
10%: entirely 10%: entirely isolatedisolated
Benkler (2006): 248-9
Summary
“Bow tie” model repeats itself within clusters
As clusters become smaller, attention is more evenly spread
Very very few are receiving no attention at all