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SNA 3A: Centrality
Lada Adamic
is counting the edges enough?
Stanford Social Web (ca. 1999)
network of personal homepages at Stanford
Y
X
Y
X
Y X
Y
X
indegree
In each of the following networks, X has higher centrality than Y according to a particular measure
outdegree betweenness closeness
different notions of centrality
Y
X
review: indegree
trade in petroleum and petroleum products, 1998, source: NBER-United Nations Trade Data
Quiz Q:
! Which countries have high indegree (import petroleum and petroleum products from many others) ! Saudi Arabia ! Japan ! Iraq ! USA ! Venezuela
review: outdegree
Y
X
Nepal
Guyana
Ethiopia
Mauritius
Mali
Lebanon
Barbados
Haiti
Cambodia
Suriname
Guadeloupe
Mauritania
Fiji
Costa Rica
Cote Divoire
Bahamas
Jordan
Angola
Nigeria
CanadaUSA
Argentina
Brazil
MexicoJapan
IranIraq Kuwait
Oman
Saudi Arabia
Untd Arab Em
China HK SAR
Korea Rep. MalaysiaSingapore
Thailand
China
Belgium-Lux
France,Monac
GermanyItalyNetherlands
Spain
UK
SwedenRussian Fed
Australia
Indonesia
Poland
Algeria
Portugal
Libya
Jamaica
Panama
Malta
India
South Africa
VenezuelaColombia
Trinidad Tbg
Bahrain
Norway
Egypt
Gabon
Guatemala
Qatar
Afghanistan
Viet NamTaiwan
Myanmar
Sri Lanka
Pakistan
Nicaragua
Korea D P Rp
Guinea
Cuba
Bangladesh
Senegal
trade in petroleum and petroleum products, 1998, source: NBER-United Nations Trade Data
Quiz Q:
! Which country has low outdegree but exports a significant quantity (thickness of the edges represents $$ value of export) of petroleum products ! Saudi Arabia ! Japan ! Iraq ! USA ! Venezuela
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trade in crude petroleum and petroleum products, 1998, source: NBER-United Nations Trade Data
Undirected degree, e.g. nodes with more friends are more central.
Assumption: the connections that your friend has don't matter, it is what they can do directly that does (e.g. go have a beer with you, help you build a deck...)
putting numbers to it
divide degree by the max. possible, i.e. (N-1)
normalization
Freeman�s general formula for centralization (can use other metrics, e.g. gini coefficient or standard deviation):
€
CD =CD (n
*) −CD (i)[ ]i=1
g∑[(N −1)(N − 2)]
How much variation is there in the centrality scores among the nodes?
maximum value in the network
centralization: skew in distribution
CD = 0.167
CD = 0.167
CD = 1.0
degree centralization examples
example financial trading networks
high in-centralization: one node buying from many others
low in-centralization: buying is more evenly distributed
real-world examples
In what ways does degree fail to capture centrality in the following graphs?
what does degree not capture?
Stanford Social Web (ca. 1999)
network of personal homepages at Stanford
Brokerage not captured by degree
Y
X
constraint
constraint
! intuition: how many pairs of individuals would have to go through you in order to reach one another in the minimum number of hops?
Y X
betweenness: capturing brokerage
€
CB (i) = g jk (i) /g jkj<k∑
Where gjk = the number of shortest paths connecting jk gjk(i) = the number that actor i is on.
Usually normalized by:
€
CB' (i) = CB (i ) /[(n −1)(n − 2) /2]
number of pairs of vertices excluding the vertex itself
betweenness: definition
betweenness on toy networks ! non-normalized version:
betweenness on toy networks ! non-normalized version:
A B C E D
! A lies between no two other vertices ! B lies between A and 3 other vertices: C, D, and E ! C lies between 4 pairs of vertices (A,D),(A,E),(B,D),(B,E)
! note that there are no alternate paths for these pairs to take, so C gets full credit
betweenness on toy networks ! non-normalized version:
betweenness on toy networks ! non-normalized version:
A B
C
E
D
! why do C and D each have betweenness 1?
! They are both on shortest paths for pairs (A,E), and (B,E), and so must share credit: ! ½+½ = 1
Quiz Question
! What is the betweenness of node E?
E
Lada�s old Facebook network: nodes are sized by degree, and colored by betweenness.
betweenness: example
Quiz Q:
! Find a node that has high betweenness but low degree
Quiz Q:
! Find a node that has low betweenness but high degree
closeness
! What if it�s not so important to have many direct friends?
! Or be �between� others
! But one still wants to be in the �middle� of things, not too far from the center
need not be in a brokerage position
Y X
Y
X
Y
X
Y
X
Closeness is based on the length of the average shortest path between a node and all other nodes in the network
€
Cc (i) = d(i, j)j=1
N
∑#
$ % %
&
' ( (
−1
€
CC' (i) = (CC (i)) /(N −1)
Closeness Centrality:
Normalized Closeness Centrality
closeness: definition
Cc' (A) =
d(A, j)j=1
N
∑
N −1
#
$
%%%%
&
'
((((
−1
=1+ 2+3+ 4
4#
$%&
'(
−1
=104
#
$%&
'(
−1
= 0.4
A B C E D
closeness: toy example
closeness: more toy examples
Quiz Q:
Which node has relatively high degree but low closeness?