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Thomas,

We have a paper coming out in the _American Journal of Sociology_ that 
addresses these types of issues. There we test the fundamental 
assumptions of Granovetter's 'The Strength of Weak Ties' and Burt's 
'Structural Holes' by combining analysis of email structure with 
analysis of email content. We ask: Which structural positions actually 
deliver the most novel information to ego?

We find that that a trade-off between network diversity and 
communications bandwidth regulates access to novel information and that 
information advantages to brokerage depend on (a) whether the 
information overlap among alters is small enough to justify bridging 
structural holes, (b) whether the size of the topic space known to 
alters is large enough to consistently provide novelty, and (c) whether 
the knowledge stock of alters refreshes enough over time to justify 
updating what was previously known. These results suggest that 
information benefits to brokerage depend on the information environments 
in which brokers find themselves.

You can find a working paper version of the forthcoming article here:

Aral, S. & Van Alstyne, M. "Networks, Information and Brokerage: The 
Diversity-Bandwidth
Tradeoff." American Journal of Sociology. In Press. Available at SSRN: 
http://ssrn.com/abstract=958158

Best

Sinan

Sinan Aral
Assistant Professor, NYU Stern School of Business.
Research Affiliate, MIT Sloan School of Management.
Personal Webpage: http://pages.stern.nyu.edu/~saral
SSRN Page: http://ssrn.com/author=110270
WIN Workshop: http://www.winworkshop.net
Twitter: http://twitter.com/sinanaral


On 4/12/2011 8:37 AM, Thomas Plotkowiak wrote:
> ***** To join INSNA, visit http://www.insna.org ***** Dear Members of 
> the SocNet List,
>
> I am looking for any papers that have computed*correlations or 
> regressions* of popular *centrality network measures* like closeness, 
> degree, eigenvector or betweeness and the *actual transmission of 
> information*.
>
> So for example I might have
>
> a) a network of friendships of peole and additionally
> b) I might have a network that has an arc if a person has forwarded 
> information from a person.
>
> If I compute a network regression of the actors degree in the 
> friendship network and the number of how often his information was 
> forwarded I can see how useful the centrality measures actually are in 
> predicting future information diffusion for an actor.
>
> I have tried that a couple of times on online friendship networks and 
> the regression usually ends up having an explanation from common 
> centrality measures are around 30%. I am wondering if there are 
> similar attempts out there in order to compare my values and my approach?
>
> I think this question is highly relevant because it actually asks if 
> the centrality measures we use every day to highlight certain actors 
> in information diffusion are really usefull.
>
> P.S.
> I can also think of computing different measures for brokers between 
> two communities and the actual transmission or strong ties and their 
> influence on the actual transmission.
>
> Best Regards
> Thomas Plotkowiak
>
> -- 
> Thomas Plotkowiak
> Research Assistant
> MCM Institute
> St. Gallen, Switzerland
> Tel +41 71 224 27 47 
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