How’s that for role reversal on Science Blogs?
Well, leave it to the good folks at Carnegie Mellon…
Scientists have long studied how information, influence or physical items move through networks. But by combining that field of research with how to optimally detect the flow in a cost-effective way, the Carnegie Mellon researchers have devised a formula, or algorithm, that could lead to dramatically improved sensor networks, whether geared toward political blogs or posture.
But how would this cascade be modeled? What sensors, or blogs in this case, should be tapped to maximize the likelihood of capturing a big story early on during its propagation over the blogosphere?
Researchers came up with a complex mathematical equation called the cost-effective lazy forward-selection algorithm, later dubbed the Cascades algorithm. It seeks to maximize reward (for blogs – detecting the most news in the least amount of time) and minimize cost (the time spent reading blogs). By utilizing the law of diminishing returns, the outcomes were calculated lists of top blogs (different results depended on the number of blogs budgeted in).
Neat, eh? If the results can be trusted, imagine the possibilities for this kind of information applied both online and in other complex systems well beyond the blogosphere…
The blogosphere as social network