Centrality measures describe a node's importance by its position in a network. The key issue obviated is that the contribution of a node to the collective behavior is not uniquely determined by the structure of the system but it is a result of the interplay between dynamics and network structure.
Here, we show that dynamical influence is a centrality measure able to quantify how strongly a node's dynamical state affects the collective behavior of a system, taking explicitly into account the interplay between structure and dynamics in complex networks.
Reductionism, as a paradigm, is expired, and complexity, as a field, is tired. Data-based mathematical models of complex systems are offering a fresh perspective, rapidly developing into a new discipline: network science.
Eh... Barabasi is really milking the golden cow :)
It seems interesting, even if I don't remember enough from my statistical mechanics classes to truly understand it without a major effort. Maybe you could make a layman's science coffee about it?
We worked on this with Luzi a few years back ... while the analogy is original and interesting it fails to capture the dynamics of a network, e.g. if a network has hubs that grow and shrink .... Luzi worked on an extended model to solve this issue, but, if I remember correctly, he got stuck in a computationally very hard problem .... We intended to develop and use the extended model to define relevant characteristic of the ESA network formed by mail exchanges.....
a new computational model that can analyze any type of complex network -- biological, social or electronic -- and reveal the critical points that can be used to control the entire system.
Slotine and his colleagues applied traditional control theory to these recent advances, devising a new model for controlling complex, self-assembling networks.
> Sounds too super to be true, no?
Yeah, how else may it sound, being a combination of hi-quality (I assume) research targeted at attracting funding, raised to the power of Science Daily's pop-pseudo-scientific journalists' bu****it?
Original article starts with a cool sentence too:
> The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them.
...a good starting point for a never-ending philosophers' debate...
Now seriously, because of a big name behind the study, I'm very curious to read the original article. Although I expect the conclusion to be that in practical cases (i.e. the cases of "networks" you *would like to* "control"), you need to control all nodes or something equally impractical...
Physicist Geoffrey West has found that simple, mathematical laws govern the properties of cities -- that wealth, crime rate, walking speed and many other aspects of a city can be deduced from a single number: the city's population. In this mind-bending talk from TEDGlobal he shows how it works and how similar laws hold for organisms and corporations.
For those who felt that Geoffrey glossed over the implications for cities and companies, the following article in the New York Times did a respectable job of drawing conclusions from Dr. West's paper:
http://www.nytimes.com/2010/12/19/magazine/19Urban_West-t.html
Tokyo has a very large population and one of the smallest crime rates in the world, in fact Tokyo is known to be the safest big city in the world (w.r.t. crime). It is hard to believe that the crime rate in L.A. is in the same order of magnitude.