Soccer and politics provide fertile ground when it comes to extreme views. A typical Corinthians soccer team fan would never publicly wear a São Paulo or Palmeiras soccer team jersey, in the same way as whoever sympathizes with liberal views would certainly refuse to vote conservative. In an attempt to understand the origin of polarized opinions and how they spread, physicist André Cavalcanti Rocha Martins, of the University of São Paulo (USP) sought inspiration in the world of atomic particles in order to create a computer program capable of representing, although in a simple manner, how people interact and exchange ideas within a community. By means of his computer method, Martins has reached the surprising conclusion that radicalism may prevail in a group even when people first tend to voice moderate ideas.
A researcher at the USP Arts, Sciences and Humanities School, Martins developed his program based on the properties of statistical mechanic properties, the field of physics that deals with the association between microscopic scale phenomena and macroscopic scale phenomena. Specifically, Martins simulated the exchange of information among people within a community based on a model of how basic particles – such as electrons – behave in a magnetic field.
One of the characteristics that can be studied during the interaction of these particles is the so-called spin, generally defined as the direction of the rotation of the electrons (clockwise or counterclockwise). “When a group of electrons is studied, a reasonable approach is to consider that some may rotate clockwise, while others rotate counterclockwise. Each particle of the sample interacts with its neighbors, and the influence of their spin and magnetic fields eventually changes its own field,” explains Martins.
Thus described, the process does not seem very different from the way a given opinion spreads among a group of people. Most of the mathematical models developed to explain this kind of situation work like this. The so-called binary models provide people with the possibility of expressing only one out of two different and generally opposing and mutually exclusive opinions: yes or no, or even, “I am a fan of São Paulo or Corinthians.” According to the continuous model, opinions are represented by a measure, usually any number between 0% and 100%, which represents an individual’s opinion. In the soccer example, it is as if a person might root preferentially for Corinthians, while also having a certain inclination for São Paulo.
When creating his own model, Martins decided to improve it by adding a certain degree of uncertainty: opinions are represented by a probability between two options – Corinthians and São Paulo – but the true opinion is not disclosed to someone who is near. “There is a probability opinion in my model, but I do not show my neighbor this uncertainty. If the probability of someone having an opinion is greater than 50%, the person interacts with his/her neighbors showing his/her preferential option. If it is below 50%, the person discloses the opposite opinion,” explains Martins.
The surprise came when he ran his program thousands of time in a row. Regardless of the initial opinion voiced by each individual, the predominating tendency was the establishment of extremist groups, with opposite opinions. In other words, it mattered little whether all the individuals began with a neutral judgment and rooted neither for São Paulo, nor for Corinthians. When interacting with the group, opinions became firm and ever more difficult to be changed, as if most of those people had become fanatical supporters of one of the teams, only a few sticking to a more moderate point of view. Martins saw an initial mix of black and white spots in the computer screen become well-defined larger stains: white or black. “Opinions became stronger and groups in which everybody thought alike were established,” states Martins, who expected a stronger influence from the system’s initial conditions upon the final result.
The physicist, who describes these results in a paper to be published shortly in the International Journal of Modern Physics C, immediately recognizes the model’s limitations to simulate what happens in the real world. The so-called contrarians – individuals who are literally “contrary,” who insist on always adopting the opinion that runs directly contrary to their neighbors’ – were not included in the simulation. “In this model, the agents are still very simple. None of them are realistic,” Martins declares. Nevertheless, the result shows that, based on simple behavioral rules related to atomic particles, it is possible to draw conclusions on the behavior of the macroscopic world. “Much as it is unnecessary to know the position of all the molecules in a glass of water in order to measure the temperature of the liquid, it is unnecessary to know the opinion of each individual to foresee how groups think,” he says.
One of the interesting premises of the study, which can represent well what happens in real situations, is that individuals interact more intensely and constantly within local groups; in other words, with neighbors. This is fertile ground for the extremist movements to emerge, according to the physicist: “These local groups only exchange opinions among themselves and remain rather closed, even if they interact with other groups around them.”
Martins is not surprised by the fact that only recently have the natural sciences started to try to deal with challenges related to human social behavior. “One cannot deny that these issues are more difficult. It is obviously easier to describe the behavior of an atom than that of a human being,” he states. “There are people who will dislike the model simply because it uses mathematics. The fact is that our field and human sciences need to interact more,” says Martins. For Martins, specialists such as sociologists may contribute significantly to these kinds of models, by creating more realistic representations of large scale or human behavior social interactions. The physicist is even a member of USP’s Interdisciplinary Information Physics and Economics Group (Grife), whose objective is to promote interaction between these fields. “We would like to understand, for instance, what results such as these can reveal about market dynamics,” he says.Republish