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The Onion clip is wonderful. Very much in snyc with the fake news
often being more informative than the real...should be required
viewing.

It seems to say a lot more than just "give observational data a
chance" to me in the context of this larger discussion. it isn't
merely that a large fraction of the phenomena we want to study occur
before we can design trials to measure them (and economists have been
dealing with this reality for decades). or that observational data are
more likely to lead to interesting discoveries of new things. Or that
whatever the methods, there are always alternative explanations,
especially when dealing with people in social settings. It's also that
if we start to believe in experiments and RCT's as the holy grail,
there's a danger of focusing too much on the kinds of questions that
lend themselves to that specific methodology, rather than going after
the ones that matter. (Even in the context of social influence in
networks.) analogously, there's a lot of time spent by research in
economics and marketing looking for "natural experiments" for
identification, and this gets to the point sometimes where it seems
like the research question was designed merely to exploit the cool
natural experiment...

i think that many aspects of this RCT vs. observational data (or for
observational data, matched-sample versus "structural" methods for
claiming causation) debates aren't unique to the context of social
influence in networks. For example:
http://en.wikipedia.org/wiki/Randomized_controlled_trial#Relative_importance_of_RCTs_and_observational_studies

cheers, Arun.

On Mon, Feb 28, 2011 at 12:40 AM, James Fowler <[log in to unmask]> wrote:
> *****  To join INSNA, visit http://www.insna.org  *****
>
> We have also relied on methods like the ones Tom Valente mentioned in many
> of our observational studies, and we summarize the pluses and minuses of
> this approach in a new paper here:
>
> http://jhfowler.ucsd.edu/examining_dynamic_social_networks.pdf
>
> I also in principle like the actor-oriented model approach of Siena, but in
> the past I could never get the model to converge for networks larger than
> 1000 nodes (this might be my own failing, though, as there is always a bit
> of art to getting models like that to work).
>
> We also have relied on experiments like this one in PNAS:
>
> http://jhfowler.ucsd.edu/cooperative_behavior_cascades.pdf
>
> and I am a big fan of David Nickerson's voter experiment and Sinan's new
> RCT.
>
> But I would resist abandoning evidence from observational studies.
>
> The resistance to observational studies reminds me of this Onion story:
>
> Multiple Stab Wounds May Be Harmful To Monkeys
> http://www.youtube.com/watch?v=S6CSIFi78Nw
>
> :)
>
> j
>
> James H. Fowler
> Professor of Medical Genetics and Political Science
> UC San Diego
> http://jhfowler.ucsd.edu
>
> CONNECTED
> http://connectedthebook.com
>
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-- 
Arun Sundararajan
Associate Professor and NEC Faculty Fellow
http://oz.stern.nyu.edu/
http://w4.stern.nyu.edu/faculty/facultyindex.cgi?id=155
"Be the change you want to see in the world." (Gandhi)

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