In an attempt to better understand the explosive nature of trends on the Internet, scientists from the University of Aberdeen have created the first-ever mathematical model to explain how things go viral.
The team used epidemic models that draw influence from the transmission of complex social phenomena and infectious diseases to create a new model that takes into consideration factors such as friends and acquaintances in its examination of the sudden spread of new ideas.
"We often witness social phenomena that become accepted by many people overnight, especially now in the age of social media," Francisco Perez-Reche, lead author of the study, said in a press release. "This is especially relevant to social contexts in which individuals initially hesitate to join a collective movement, for example a strike, because they fear becoming part of a minority that could be punished. But it also applies to new ideas or products."
Past mathematical models that tried to understand the process failed to account for the synergistic effects of acquaintances and ultimately failed to explain the contagious nature of ideas that spread throughout cyberspace.
"In very basic terms our model shows that people's opposition to accept 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," Perez-Reche said.
Although the team acknowledges the importance of social media for this process, they also focus on the intrinsic value of the idea or product and acceptance of it from friends or acquaintances.
The team believes that the model could be used to address social issues as well as help companies give their product an edge over competing products.
"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," Perez-Reche explained.
He added: "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."
The findings were published in the Jan. 28 issue of Scientific Reports.