Network Analysis:
What it is, what it isn’t, and how you do it.
Alexander H. Montgomery
Reed College
Network Analysis (NA)
•
•
•
•
What is (and is not) NA in IR
How to do NA (in three parts)
NA: The Good, the Bad, and the Ugly
Questions
What is (and is not) NA in IR
• “Networks” in IR (not NA)
– TANs, CTAs, Networked
Governance
– Hierarchies/Networks/Mark
ets
• Networks as Relational
Structures (NA)
– Individualist Explanations
– Holist Explanations
– Relationalist Explanations
I am A, so
A>B
I do B.
HOLIST
STRUCTURE
RELATIONS
How to do Network Analysis (1)
1. Define your networks
– Ties
– Nodes
2a. Theorize network
dynamics
– Tie-based
• Structural Balance
• Structural Equivalence
• Preferred Attachment
– Node-based
• Homophily
• Heterophily
USA
4
France
1
China
2
1
N.Korea
1
Iran
Pakistan
How to do Network Analysis (2)
2b. Theorize network effects
– Individual/Interaction Level:
Social Capital/Power
• Access
• Brokerage
• Exit
– Group Level: Conflict and
Cooperation
– Network Level: Efficiency
and Robustness
USA
4
France
1
China
2
1
Iran
1
N.Korea
How to do Network Analysis (3)
3. Measure and analyze
– Conceptual
– Graphs
OTHER
PEACE AND SECURITY
ARMS CONTROL
ENVIRONMENT
DEVELOPMENT
HUMAN RIGHTS
HUMANITARIAN
CROSS−CUTTING
GOV
IO
INGO
NGO
UN
achpr.org
fidh.org
apt.ch
minorityrights.org
iidh.ed.cr
humanrightsfirst.org
omct.org
icj.org
icc−cpi.int
alhaq.org
cajpe.org.pe
cpj.org
amnesty.org aprodeh.org.pe
echr.coe.int
derechos.org
aohr.org
ohchr.org
coe.int
corteidh.or.cr
icj−cij.org
hrw.org
crin.org
oas.org
actionaid.org
ictr.orgunmillenniumproject.org
icrc.org
womenwarpeace.org
icbl.org
millenniumindicators .un.org
alertnet.org
who.int
irinnews.org
icrw.org
iom.int
genderandaids.org
reliefweb.int
unifem.org
unodc.org
unfoundation.org un−instraw.org
unescap.org
ifrc.org
unaids.org
mineaction.org
unfpa.org
unifem.undp.org
ausaid.gov.au ochaonline.un.org
uneca.org
ilo.org
wedo.org
unicef.org
unece.org
iadb.org
escwa.org.lb
unmikonline.org
undp.org dfid.gov.uk
unhcr.org
unv.org
wfp.org
unep.org
unesco.org
fao.org
imf.org
undg.org
wto.org
ifad.org
imo.org
unitar.org
unctad.org
unido.org
unhabitat.org
unfccc.int
How to do Network Analysis (3)
Cluster 1
20
3. Measure and analyze
–
–
–
–
USA(89)
FRN
Conceptual
(120)
Graphs
Calculate Quantities
Regression
69
61
63
AUS(78)
JOURNAL OF CONFLICT RESOLUTION
In this diagram, lines are labeled with
number of IGO
BRA
51
memberships
between
states. Each
Effects of Intergovernmental
Organization
Social
Networks
(74)
47the Predicted Probability of a Militarized
state is labeled
with
its total
number
on
Interstate
Dispute
(MID)
41
of IGO memberships. Note that the
Probability
three states on the
left (USA,Percentage
France,
an MID Change in Risk a
38
45
Australia) form aofclique
of states with
ties above 60. The.0024
two states on the
Baseline47
(all variables at their mean)
right
(Brazil,
China)
are close to
CHN(59)
45 ij
CLUSSAME
structurally
equivalent
Minimum value (0)
.0025 to each other;
+4
Maximum value (1)
.0021 ties to–13
they have similar valued
other
PRESTIGED
states.
the2common
TABLE
Minimum value (0)
.0029
+21
Maximum value (101.82)
.0006
–75
CLUSSIZEH
Minimum value (2)
.0017
–29
Maximum value (86)
.0030
+25
Idealcluster
networkmembership
types
Figure 1a: Measuring ties and
from IGO membership. Data is from 1992.
Social rivals:
minimum and
CLUSSAME
PRESTIGE
,
ij, minimum
(Countries are placed for readibility;
distances
placement
do not
have Dany
meaning)
maximum CLUSSIZEH
.0040
+66
Social allies: maximum CLUSSAMEij, maximum PRESTIGED,
minimum CLUSSIZEH
.0004
–83
DEML
This diagram demonstrates
how+46
Minimum value (–10)
.0036
prestige is calculated.
Maximum value (10)
.0010Each country's
–54
DEPENDL
influence on another country is
BRA
USA(2.81)
Minimum value (0)
.0025 the number
+4 of
calculated by dividing
(2.13)
Maximum value (.21)
.0000
–100
.775
FRN
(3.01)
.808
AUS(2.53)
.635
IGOs in common by the total number
of estimates
IGO memberships
in the
influenced
NOTE: These probabilities are calculated using the logit
in column 2 of Table
1. Unless
otherwise
specified, all variables are held at their means.
state. Only the influence of the
a. Percentage change in MID risk is computed as the percentage change from the baseline.
country on the far left (France) on
other countries
is shown.
The prestige
We incorporated measures of interest similarity;
we found that
the inclusion
of these
CHN(1.99)
39far left (if only
of
the
country
on
the
measures never affected our results statistically or substantively. We tried alternate
four countries
weremaximum,
added up)and
is,sum of
specifications of our prestige variable, including
the minimum,
therefore,
3.01.
two countries’ prestige; while in the base model, all reduced conflict, none were as
.796
robust in additional tests as the difference between two countries’ prestige values, bol40
stering
ourIGO
proposition
that relative
suppress are
conflict.
We
Figure 1b: Measuring prestige
from
membership.
Dataprestige
is fromdifferences
1992. (Countries
placed
foraltered
our clustering
variables,
including
using the distance matrix directly instead of our
readibility; distances and placement
do not
have any
meaning)
CLUSSAME variable and a constant rather than a smoothly increasing number of
NA: The Good, the Bad, & the Ugly
• Explicit
– Trade (1947-2000)
(Ward and
Hoff 2007)
– Diplomatic Relations (18172005)
• Affiliation
– IGOs (1816-2000)
– Alliances (1816-2000)
(Maoz 2006)
• Implicit
– Democracy, Religion,
Ethnicity, etc.
• Interactions
– MIDs, War, etc.
(Lewer and Van
den Berg 2007)
Questions?