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Online Social Networks can be Tipped by as Little as 0.8% of their Population

Anonymous Coward writes | more than 2 years ago

Social Networks 0

An anonymous reader writes "A new algorithm developed by researchers at West Point seems to break new ground for viral marketing practices in online social networks. Assuming a trend or behavior that spreads in an online social network based on the classic “tipping” model from sociology (based on the work of Thomas Schelling and Mark Granovetter), the new West Point algorithm can find a set of individuals in the network that can initiate a social cascade – a progressive series of “tipping” incidents — which leads to everyone in the social network adopting the new behavior. But the real good news for viral marketers is that this set of individuals is often very small – a sample of the Friendster social network can be influenced when only 0.8% of the initial population is seeded. The trick is finding the seed set – which the West Point algorithm often does in only a few minutes. The algorithm is described at a paper to be presented later this summer at the prestigious IEEE ASONAM conference. A copy of the paper is available at http://arxiv.org/abs/1205.4431. Further info on this new algorithm can also be found at http://blog.netsciwestpoint.org/2012/05/30/online-social-networks-can-be-tipped-by-as-little-as-0-8-of-their-population/."
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