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Thanks for pointing out the importance of this issue
I would add to this bibliography the following articles:
This article designs a definition of local leader and states:
"Our results show that social leaders that have the MMS technology (i.e. the
possibility to send image files) are two times more successful in infecting
their community with that technology than the customers that have a similar
profile but are not social leaders."
This is an argument suggesting that taking the network into account can be
useful in marketing.
V. Blondel, C. De Kerchove, E. Huens, P. Van Dooren, "Social leaders in graphs", Positive Systems, 231--237, 2006, Springer
Besides, even if there is no causation from network to characteristics (but mere
correlation), the network can be a lot easier to measure than the characteristics:
"We consider a setting where the topology of the network is known, but the class
labels of the nodes are not. This could be the case, for instance, if we have a
network of blogs and hyperlinks between them (like citations, trackbacks,
blogrolls, etc.) and we are trying to classify the blogs according to their
political leaning. Another possible application is in online social networks,
where friendships are known and we are trying to infer hidden demographic
A strategy is then to measure the whole network, measure the characteristics of
a few well chosen nodes, and infer the characteristics of the other nodes.
C. Moore, X. Yan, Y. Zhu, J.-B. Rouquier, and T. Lane. "Active learning for
hidden attributes in networks." In /KDD (International Conference on Knowledge
Discovery and Data Mining)/, 2011. Accepted
So even in a setting where the network is entirely determined by the
characteristics of each node, network theory can still matter.
Thus, I hope we still have a job for some time ;-)
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