Online Social Networks Can Be Tipped By Less Than 1% of Their Population

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. The 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. The algorithm is described in a paper to be presented later this summer at the prestigious IEEE ASONAM conference."

Comments

It all makes sense

[Sparticus789]

Is this what Occupy means when they say 1% of the country controls everything?

Re:Wow, Friendster? All 300 Users?

[CohibaVancouver]

Friendster? Wow, you could influence, like, 300 people

American-centrist much, you insensitive clod?

From http://en.wikipedia.org/wiki/Friendster

Since the relaunch of Friendster as a social gaming platform in June 2011, the number of registered users has reached over 115 million. Over 90% of Friendster's traffic came from Asia. The top 10 countries accessing Friendster, according to Alexa, as of May 7, 2009 are the Philippines, Indonesia, Malaysia, Singapore, Thailand, Pakistan, United Arab Emirates, Sudan, South Korea, Bangladesh and India

The trick is not just finding the seed set

[timeOday]

"The trick is finding the seed set." No, you still have to influence the seed set, which might be really hard.

Let's say this model predicts that I can end terrorism by converting 100 radical muslims to buddhism. How does that help me? (Simply sending in drones to remove these nodes from the graph, so to speak, will not have the same effect).

Second example, let's say my novel is almost guaranteed to be successful if it gets a glowing review in the New York Times. Well, how hard can that be? Usually trusted nodes are trusted for some reason - because they're reliable. That means they're hard to influence.

Algorithm is very simple

[mrops]

I looked at it, and it looks like this

public static boolean willTip(User user) {
  if(user.sex == SexType.FEMALE && user.hotness>(Long.MAX_VALUE-100)) {
      return true
  }
  return false;
}