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Hi Balazs -

I agree w. David that you need to start with a definition of cohesion 
and then ask how that changes over time.

Doug White & I propose using node-connectivity as a measure of 
structural cohesion. It has some nicely intuitive properties that 
capture much of what theorists often mean by structural cohesion 
(see: Moody, James and Douglas R. White. 2003. 
Cohesion and Embeddedness." American Sociological Review 
68:103-127).  If you want to then treat "dynamic" as successive (or 
overlapping) time slices of your network, then you can simply 
calculate the cohesion for each time frame and map it's change in 
levels over time.

However, a key feature of this notion of cohesion is that it focuses 
on the node-independent path structure of the graph -- the multiple 
ways that people can reach each other through the network without 
that reach being uniquely controlled by a single (or small number of 
) actor(s).  An interesting aspect of a truly dynamic graph is that 
the ordering of relations will shape flow through the 
network.  Effectively, all "flow" has to go downstream in time, with 
local "reversals" possible when you have concurrent 
relations.   Since it is possible to identify these time-ordered 
paths (Moody, James. 2002. 
Importance of Relationship Timing for Diffusion: Indirect 
Connectivity and STD Infection Risk" Social Forces 81:25-56), in 
principle you could define a "common history of cohesion" through the 
pattern of time-specific reachability (though I know of no 
implementations of this, yet).

If you wanted to map the changing patterns of coalitions over time, 
you might imagine treating "groups" as a class of nodes in a dynamic 
two-mode network.  At each time slice (whatever time is relevant 
here), you assign nodes to "peer groups" (again based on your 
context-relevant definition).   You could then look at the one-mode 
(presumably person) projection of this graph, which would effectively 
show you the history of group co-membership over the life of your 
network.  The resulting structure of this graph might be very 
informative:  if you imagine people cycling though many groups then 
the resulting projection will probably admit to few factions, if, on 
the other hand, time-local groups are really embedded in a larger 
constant coalition of units, this will come out in the 
group-co-membership network as clear divisions.

And, of course, if you want to simply explore the dynamics of your 
graph visually, you might want to check out SoNIA:

All the best,

At 02:33 AM 12/20/2005, you wrote:
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>Dear Socnetters,
>I wonder if anyone had experience with identifying cohesive groups in
>dynamic network data.
>How would you identify a group as a common history of cohesion rather than a
>cohesive subset in a network snapshot?
>Any comments are appreciated,
>SOCNET is a service of INSNA, the professional association for social
>network researchers ( To unsubscribe, send
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James Moody
Associate Professor
Department of Sociology
Ohio State University
372 Bricker Hall
190 N. Oval Mall
Columbus, OH 43210

(614) 292-1722
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