In the November issue of Popular Science (yes, sometimes I do more than look at the pictures!), there’s a great article about one of the world’s foremost network theorists, Albert-Lazlo Barabasi. He recently developed a program, which using cell towers as nodes, allowed him to predict, with 93% accuracy, an individual’s location within one square mile.
Then, combining particle physics and control theory, he has begun the development of an algorithm that “runs through an entire network over and over again until it finds the minimum set of starting points needed to reach every node in the system. Control these starting points, and you control the entire system.” This algorithm has been tested on a variety of networks including a constellation of alliances in a prison population (probably association members who didn’t pay their dues), the metabolic pathways in yeast, and several internet communities including Slashdot and Epinions. Though it has a way to go (more data points needed), this concept, if applied to our association systems, could radically change the way associations interact with members…and vice versa.
Pie-in-the-sky or right around the corner? We’re collecting member datapoints at an exponentially increasing rate and our ability to apply predictive science to these datasets may be much closer at hand than one expects. Data Rules! “Resistance is futile.”