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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.

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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