Scientists for the first time have created a mathematical model for how memes spread across social media. The international team constructed the model based on how epidemics spread; its not a coincidence that things are said to go “viral.”
The main finding is that something goes viral thanks to the initial combined effect of many people. Most individuals wont share it straight away, so they form a barrier thatneeds to be overcome. Once the barrier has been breached, if friends start sharing a story for example, then it explodes, spreading exponentially.
We often witness social phenomena that become accepted by many people overnight, especially now in the age of social media, Dr. Francisco Perez-Reche, co-author of the paper, said in a statement.
This is especially relevant to social contexts in which individuals initially hesitate to join a collective movement, for examplea strike, because they fear becoming part of a minority that could be punished.But it also applies to new ideas or products.
The quick spread of ideas might seem like a recent phenomenon, but the Internet has simply made the transmission more evident. The word meme itself was coined by biologist Richard Dawkins in 1976, long before the first cat was shared over the web.
The researchers showed that the most important factors are the intrinsic value of the idea and the adoption by trustworthy virtual neighbors. This could explain why marketing campaigns engineered to go viral tend to backfire spectacularly.
In very basic terms our model shows that peoples opposition to accepting a new idea acts as a barrier to large contagion, until the transmission of the phenomenon becomes strong enough to overcome that reluctance at this point, explosive contagion happens, he added.
The research, which is published inNature Scientific Reports, connects what happens at a very local level to the general spread. This model could be used to better address social issues and even for better advertising strategies.
Our conclusions rely on numerical simulations and analytical calculations for a variety of contagion models, and we anticipate that the new understanding provided by our study will have important implications in real social scenarios, he explained.
For instance, it could lead to better strategies to minimize the risk of sudden and often unexpected epidemics of undesired social behavior.Similarly, it will suggest methods to engineer explosive diffusion of innovative products and ideas.”