Predict human population sizes with physics

Just by knowing the average number of friends each person has, scientists at the Complexity Science Hub (CSH) have been able to predict the group sizes of people in a computer game. For this purpose, they modeled the formation of social groups on an example from physics, the self-organization of particles with spin.

Sociologists have focused on how social groups They and the mechanism behind them are formed for a long time. The desire to avoid tension, as well as homosexuality—the tendency of people to join groups with others who share similar traits, traits, or opinions—have been observed in many different contexts.

Although multiple models have been studied, little is known about how sexuality and stress avoidance influence human group formation, and in particular Distribution size Of them – whether there are many small group Or a few, for example,” explains Jan Korbel of CSH and first author of the study. Using two contemporary areas of physics, called self-assembly and spin glasses, scientists are now shedding new light on social group formation.

Cognitive challenges of people in groups

One defining characteristic of humans is that they organize themselves (often for specific purposes) into groups. “The difficulty here is that this needs coordination, which takes a lot of effort,” says CSH’s Stefan Thurner. “As groups grow in size and internal conflicts arise, coordination can quickly reach and transcend the cognitive limits of humans.”

“Therefore, there must be specific mechanisms that enable humans to organize into groups efficiently. And they must be explainable with some very general human behavioral traits, such as homosexuality and the tendency to avoid stress within groups,” Thorner continues.

People behave like particles with spin

Social groups usually appear when people with similar opinions begin to interact with each other. In previous studies, we have studied self-assembly of nanoparticles in small thermodynamic systems, where they spontaneously form higher-order structures without any external interferences. Then we realized: This is similar to what people do,” Korbel recalls.

People interact with each other, and the clusters appear very similar to the particles that make up colloids or polymers. Motivated by this, the research team developed a simple model of homophilic humans based on self-organizing mechanisms of spin particles.

Small information, big results

This model was able to predict the group size distribution in Pardus multiplayer online game. “Usually, you need to know the structure of the network and how it is designed,” Korbel explains the findings.

“Here we just need to know the average number of friends a player has.” Using this relatively small amount of information, the researchers were able to predict how many clusters of a given size would appear.

Principal quantities in social systems

“Of course, people are more complex than particles, but certain types of interactions between them are similar, in particular the number of possibilities that a group of people can form combinations. This number is called the entropy, and it’s our starting point for modeling mathematics,” says Thorner.

There were stages when people tended to form large groups, but there were others when it didn’t because opinions were so different. “Becoming a member of a large group would have been a huge social pressure for them in that situation,” Corbel says. Besides entropy, this social pressure is the other key quantity here – a fundamental quantity comparable to energy in physics. The more similar the people in the group, the less social pressure they may experience.

From magnets to opinions

From a physical point of view, this can be compared to rotation: while in magnets all rotations point in the same direction, in rotating glass, which are alloys of metals and non-metals, they are disordered. Because of that complex structure, spinning in a state of “stress”, because it has to align with many other spins, and it cannot do so at the same time. “This is like a group with different opinions. You can’t get along with all of them, and you might get frustrated,” Corbel draws the comparison.

“Interestingly, very different systems can have the same expression of entropy. In our case, social individuals seem to have entropy similar to structure-forming systems, such as some spin glasses,” Thorner says.

Korbel concludes, “Our new model can help predict phenomena from sociology regarding social networks and media that lead to social frustration and polarization.” It also shows the potential of interdisciplinary research approaches, which are particularly appreciated in the Center for Complex Sciences.

“The vision is to finally have more quantitative models that can be tested on real data about how Homo sapiens organize themselves into groups, perhaps the best thing we do as a species,” adds Thurner.

Research published in Physical review letters.