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=========================================
Tom A.B. Snijders
Professor of Statistics and Methodology, Dept of Sociology, University of
Groningen
Emeritus Fellow, Nuffield College, University of Oxford
http://www.stats.ox.ac.uk/~snijders

On Mon, May 23, 2016 at 9:08 PM, martina morris <[log in to unmask]>
wrote:

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> Sender:       Social Networks Discussion Forum <[log in to unmask]>
> Poster:       martina morris <[log in to unmask]>
> Subject:      Re: Social network forecasting
>
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>
> I'm not sure your characterization about social network analysis being not
> dynamic is correct.  There's a great deal of work being done on dynamic
> SAOMs (see Snijder's work and Sienna software) and temporal ERGMs
> (TERGMs, see Hanneke & Xing, and Krivitsky and Handcock, and the tergm
> package in statnet software).
>
> We are  using STERGMs to estimate network patterns from egocentrically
> sampled data, and then simulate dynamic networks from the model, as a
> basis for studying how HIV spreads through contact networks.  The approach
> is currently being used by the CDC for their projections of the
> effectiveness of alternative HIV prevention strategies.
>
> Martina
>
> On Mon, 23 May 2016, Thomas Ball wrote:
>
> > ***** To join INSNA, visit http://www.insna.org ***** Social network
> analysis is, for the most part, not dynamic. An
> > important exception in this regard is the work being done by Iman van
> Lelyveld in dynamic mapping of the relationships
> > between and among Europe's Central Banks.
> > What other work on dynamic social network analysis is being done? Are
> protocols being developed that perform
> > forward-looking forecasts?
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