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Make it Tip in your Favor

How do rumors spread? How do dictators that were in power for decades suddenly get overthrown? What led to the rapid rise of Hush Puppies in the 1990s? Malcolm Gladwell attempted to explain how social epidemics spread in his book, “The Tipping Point”. He did not, however, explain when this “tipping point” occurred.

Why is it that only some ideas make it big? Understanding this critical point would help determine the number of people you need to convince to be able to spread your beliefs to the rest of the population. One would expect the answer to lie in the dynamics of social networks, in the strength of ties between people and the kind of relationships that exist. However, scientists at Rensselaer Polytechnic Institute have recently discovered that it only takes 10% of the population with an unshakable belief to make the majority adopt it.

In the study, scientists developed computational models of different social networks. The nodes in the network represented people in the social setting. In one network, every node was connected to every other node. In another, some people were ‘leaders’ and connected to a large number of nodes. The third model involved each node having approximately the same number of connections. Initially, each person held an opinion but was open to other ideas. As shown in the figure, a few people that hold the new idea and randomly positioned in these networks. Unlike the traditional view holders with an open mindset, these people are highly opinionated and are set in their beliefs. As these true believers become to converse with the rest of the population, the number of people that hold the new idea continues to increase gradually until 10% of the population believes in the new idea, after which it spreads like fire.

The interesting observation from this experiment is the fact that this 10% tipping point is independent of the type of network it is tested in. The results, as the study states, would have major implications in understanding social interactions ranging from acceptance of new discoveries by the population to political movements. It would help in emergency evacuation situations to inform people efficiently.

Using graph theory and social network analysis would help develop a more accurate model. For instance, the current model assumes everyone as a traditional view holder, with an unbiased opinion. It does not consider the strength of ties between people to determine the pace at which new ideas are communicated. Further, it does not account for positive and negative ties between people, as negative ties could lead to discouragement in the spread of this belief. It would be exciting to combine this new discovery with the science of information networks to determine if the tipping point remains consistent in these new hypothesized environments.

The research could be joined with other social sciences to better understand historical events. For instance, it would be interesting to use this to study Stanford’s ‘Mapping the Republic of Letters’ project that maps thousands of letters that were exchanged during the period of the Enlightenment to understand the correspondence of various writers, philosophers and scientists at the time.





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