HMN 2025: How to Map out the hidden mechanics behind why some fads spread like wildfire

Whether it is a whole friendship group migrating to using iPhones or a swath of classmates wanting the latest Lululemon waterbottle, network scientists have uncovered the hidden mechanics behind social trends.

In a study by the London team at Northeastern University, researchers have shown how mass social contagion can spread like wildfire when behavior or infection occurs through several group and pair interactions.

Professor Istvan Kiss, who led the research, says it is clear that someone might decide to adopt the same things as their friends with whom they spend time in groups and then in one-to-one situations. If friends are sharing photos on iMessage, then it is natural for others to migrate to do the same.

But coming up with the mathematical formulas to back that up was its own undertaking.

How group and pair interactions fuel contagion

The research unpacks how people interact in multiple groups and how these can overlap with each other at times. By studying data sets where people interact in groups and where some then also meet in pairs, they found that such conditions roll the pitch for a possible explosion in contagions.

As pairs of people meet up, the contagious illness or behavior can spread between them, Kiss explains. As these two people then interact in groups, either together or separately, this helps to spread it further. The more groups they are in, the further the infection is likely to travel.

“That is when the situation can lead to an explosion,” says Kiss, a member of the Network Science Institute in London. Kiss describes it as being akin to a spring being tightly loaded—the more interactions between pairs and groups where the same behavior is being exhibited, the more aggressive the final release is going to be among the public.

The findings are set out in a paper, “Disentangling the role of heterogeneity and hyperedge overlap in explosive contagion on higher-order networks,” which has been published by the Physical Review Letters journal.

While Kiss, who is scheduled to publish the second version of his book, “Mathematics of Epidemics on Networks,” says the paper was designed to be a theoretical exploration of the concept, he points out that it could have wider implications for social studies.

“It is about understanding the way people cluster, the way these groups are and how they overlap,” he says. “So when you can have two, three or even multiple people featuring in different groups of different sizes, then this is absolutely fundamental in understanding when a new idea, a new adoption or a new fashion might or might not transmit.”

The paper, he adds, helps to unpack how that transmission process happens, at what speed it is likely to spread and the stages involved in that illness or social idea mushrooming.

Implications for social contagion research

An explosive contagion has been observed before in the field of network science, Kiss says. But the idea with this latest study was to go further by striving to understand the role that overlapping group interactions have on the concept. They found that the higher the overlap, the easier it is to start an epidemic.

A co-author of the paper, Iacopo Iacopini—an associate professor and fellow member of the Network Science Institute in London—helped formulate the research.

Kiss says it was a paper his colleague produced in 2019, titled “Simplicial models of social contagion,” that served as an inspiration to pursue the project.

Iacopini explains that his work six years ago discovered that group exchanges can “cause sudden jumps, from no spreading to epidemic states.” It identified conditions where there could be no adoption of a phenomenon to suddenly move to a widespread take-up.

This latest research undertaking “goes much deeper” than that original work, however, he states, with the new calculations “mapping out the hidden mechanics” that lie behind the fast-acting social and medical situations that we observe in society.

“This gives us a much more detailed and exact picture of what’s going on,” says Iacopini. “With a far too stretched baking analogy, it’s like the difference between knowing that bread rises and understanding exactly how temperature and humidity in the oven, on top of ingredient ratios, control whether you would get a perfect loaf or flat shoe sole.”

This story is republished courtesy of Northeastern Global News news.northeastern.edu.

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