First, get “sheeple” hooked on social media. Analyze networks and behavior. Then manipulate to your will:
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“A less investigated problem is once you’ve identified the network, how do you manipulate it toward an end,” said Warren Dixon, a Ph.D. in electrical and computer engineering and director of the University of Florida’s Nonlinear Controls and Robotics research group. Dixon was the principal investigator on an Air Force Research Laboratory-funded project, which published its findings in February in a paper entitled “Containment Control for a Social Network with State-Dependent Connectivity.”
The research demonstrates that the mathematical principles used to control groups of autonomous robots can be applied to social networks in order to control human behavior. If properly calibrated, the mathematical models developed by Dixon and his fellow researchers could be used to sway the opinion of social networks toward a desired set of behaviors—perhaps in concert with some of the social media “effects” cyber-weaponry developed by the NSA and its British counterpart, GCHQ.
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The language that was being used to mathematically describe the interactions [between people and products] was the same language we use in controlling groups of autonomous vehicles.”
The social drone graph
That language was Graph theory—the mathematical language that is the basis of Facebook’s Graph database and the “entity” databases at the heart of Google and Bing’s understanding of context around searches. It’s also become a fundamental part of control systems for directing swarms of autonomous robots. The connection inspired Dixon to want to investigate the connection further, he said. “Can you apply the same math to controlling autonomous people to groups of people?”
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Full story at arstechnica
