***** To join INSNA, visit http://www.insna.org ***** 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. "<http://www2.asanet.org/journals/ASRFeb03MoodyWhite.pdf>Social 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. "<http://muse.jhu.edu/journals/social_forces/v081/81.1moody.pdf>The 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: http://www.stanford.edu/group/sonia/ All the best, Jim At 02:33 AM 12/20/2005, you wrote: >***** To join INSNA, visit http://www.insna.org ***** > >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, > >Best >Balazs > >_____________________________________________________________________ >SOCNET is a service of INSNA, the professional association for social >network researchers (http://www.insna.org). To unsubscribe, send >an email message to [log in to unmask] containing the line >UNSUBSCRIBE SOCNET in the body of the message. James Moody Associate Professor Department of Sociology Ohio State University 372 Bricker Hall 190 N. Oval Mall Columbus, OH 43210 (614) 292-1722 [log in to unmask] http://www.soc.sbs.ohio-state.edu/jwm/ _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.