Title: Quantitative Network Analysis: Perspectives on mapping change in world system globalization
1Quantitative Network Analysis Perspectives on
mapping change in world system globalization
- Douglas White
- Robert Hanneman
2The Social Network Approach
- Structure as
- Nodes and edges, or
- Actors and relations
- Dynamics as
- Agency bottom up building of ties, but
- Embedding within the emergent constraints of
macro-structure
3Structure
- Nodes can be individuals, organizations,
locations, or analytical aggregates - Relations can be material exchange, information
flow, or shared status - What is fundamental are the ties or absence of
ties between actors, in addition to the
attributes of the actors
4I. Network structures in the world system
- Commodity chains
- Trade systems, transport and communication
- Business networks
- City systems
- Interstate power
5Commodity chains
Whites analysis of the input-output matrix of
the Danish economy seen as a network scaled
by equivalence of position. (available for the
U.S., U.K, Holland, Italy, France, Australia)
6Transportation and communication
- Volume, speed, cost of movement of
- Bulk goods
- Luxury goods
- Information
- Between
- Spatial locations
- Population centers
- Organizations/states
7Trade network (13th century)
8Business networks
- Corporate interlocks
- Market exchanges
- Shared technology (e.g. licensing)
- Shared niche space
- Business groups
Evolution of the interorganization contracts
network in biotech RD and VC links for 1989
1999 (Powell, White, Koput and Owen-Smith
forthcoming, AJS)
9City systems
Settlement systems have been seen as systems that
evolve toward hierarchical networks. Networks
like this may have an exponential degree
distribution.
10Interstate power
- Treaty/alliance networks
- Exchange of recognition
- Bloc membership
- Co-membership in supra-national organizations
11II. Summarizing structures
- Density, degree, reach
- Centrality and power
- Cohesion and sub-groups
- Positions and roles
12Density, degree, reach
- How much connection is there?
- Which nodes have how much connection (social
capital)? - Which actors are closest to, most influenced by
which others?
13Centrality and power
- Which actors have most ties?
- Which actors are closest to most others?
- Which actors are between others?
14Cohesion and sub-groups
- Are there blocs or factions or sub-groups?
- Which actors are connected, how tightly, to which
groups? - What roles do actors have with respect to
relations between groups? - Level of cohesive membership as a predictive
variable
(Predictive Structural Cohesion theory)
15Roles and positions
Regular equivalence of positions in the 13th
century main European banking/trading network
- Can actors be classified according to which other
actors they have ties to? - Can actors be classified according to which other
kinds of actors they have ties to? - Actors roles in the structure (e.g. core
nation)
Same scaling method as Smith and White 1992 that
showed a virtually linear core-periphery
structure in the contemporary world-trade system
16III. Dynamics
- Actors make relations
- Relations condition actors
- Micro?macro links between probabilistic
attachment bias and network topologies - Macro?micro effects of network topologies on
actor activities and behaviors
17III. Network dynamics in the world system
- How and why do world systems expand, contract,
and change structure? - Homophily
- Exchange
- Power-laws (degree preference)
- Cohesion and shortcuts
18Homophily
- Forming (or breaking) ties is not random
- Actors may have preferences to form (or sustain)
ties with similar others - The macro-result is local clustering and
formation of factions
19Network exchange
- Ties may be formed (or dissolved) proportional to
the cost/benefits to actors, and - Constraints due to presence of relations and
existing embedding (alternatives available to
each actor) - Macro-result may tend to structural holes and
extended networks
20Power laws
- Actors with ties may use ties as social capital
to accumulate further ties, and - Actors with few ties may prefer to establish ties
with actors with more ties - Both tendencies have the macro-result of
exponential distributions of ties - Exponential networks create relatively short
average path-lengths (shortcuts) unless the hub
distributions are too extreme
21Examples of scale-independent networks and
effects on alpha
- Proteome yeast alpha2.4 (Amaral) hierarchical
organization, reduces alpha
Greek Gods alpha3.0 (HJ Newman) with no real
organizational constraints, pure 'scale free'
alpha (courtesy B. Walters)
Biotech alpha2.0 (Powell, White, Koput,
Owen-Smith) cohesive organization, reduces alpha
22Cohesion and shortcuts
- Competing tendencies toward closed and cohesive
local structures and - Extensive short-distance structures
- Lead to mixed models, such as
23Ring Cohesion
- Cohesion is an important predictor of network
attachment, demonstrated in schools (AdHealth),
industry (e.g. biotech), kinship, social class,
and other fields and organizations. Ring cohesion
theory focuses on preferential attachment-to-cohes
ion mechanisms and how they are constructed. - Ring cohesion analysis has now been completed for
biotech and numerous kinship examples (work
underway with Wehbe, Houseman) and is being done
on the 13th C. world-system networks
24Further applications of ring cohesion
- Nord-Pas-de-Calais study spatial and
kin-connected dimensions of ring cohesion (joint
scaling model with Hervé Le Bras) - Networks of the previous world-system (13th
century trade and monetary linkages with Peter
Spufford) - Networks of the first world-system (Jemdet Nasr
Henry Wright)
25IV. Conclusions
- How networks are formed (probabilistic biases),
how multiple networks and levels interlock, what
is transmitted has powerful predictions, - Including micro-macro (predictive linkages) with
more global structural and dynamical properties
of networks and their structural transformations - With macro?micro feedback for quantitative
changes and qualitative transformations of
systemic properties at the level of local
interaction