Print

Print


***** To join INSNA, visit http://www.insna.org ***** 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:
[log in to unmask]" type="cite">***** 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
_____________________________________________________________________ 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.
_____________________________________________________________________ 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.