Societies are becoming increasingly divided, and extremist views continue to emerge around the world on topics such as politics, religion, and climate change. Much research has been done into how this phenomenon known as “polarization” evolved, but it is unclear how social interactions can cause the opposite effect, “depolarization”. Less attention has been paid to understanding whether gender exists. Start modifying your opinions so that they are no longer extreme.
To address this question, Jaume Ojer, Michele Starnini and Romualdo Pastor-Satorras from the Fisica Department, CENTAI Institute in Turin, Polytechnic University of Catalunya, are developing a new “ We proposed a “Social Compass” model.Extremist positions and how the polarization of these opinions can be resolved1. Their theoretical framework is validated through extensive numerical simulations and tested using poll data collected by the American National Election Study.
Multiple subjects for one opinion
“Polarization contributes to widening political disparities in society and can impede collective solutions to important social challenges,” the researchers said. “It may even facilitate the spread of misinformation and conspiracy theories. Our depolarization framework may provide a solution to these social ills.”
Models explaining polarization are based on mechanisms as diverse as homosexuality, limited trust, or rejection of opinions. Until now, the process of depolarization in groups has generally been modeled on the simple case of an individual’s opinion on a single subject. But in reality, individuals have opinions on multiple subjects at any given time. Therefore, a multidimensional modeling framework is needed to better explain how opinions evolve.
When multiple subjects are considered, many features emerge. The first is coherence, that is, the existence of correlations between opinions on different subjects. For example, people with strong religious beliefs are more likely to oppose abortion laws. The problem with current multidimensional models is that they ignore the interdependence between different subjects. In other words, it is not possible to clearly describe the polarization of opinions.
social compass model
The key idea of the social compass model is to express opinions in relation to two topics on opposite sides of a polar plane. The angle of the plane represents an individual’s orientation toward the two topics, and its radius represents the strength of the attitude (or “belief”).
“This bipolar representation naturally allows us to formulate a key hypothesis of our model: that hardliners with extreme opinions (or strong beliefs) It means that they may be less likely to change their opinion than individuals,” explains Michele Starnini. This hypothesis is intuitive and consistent with observations in experimental psychology. “Such polar representations are very common in physics, but less common in the social sciences.”
Inspired by the Friedkin-Johnsen model2, researchers studied how social influences influence an individual’s initial opinion. They found that their model describes a phase transition from an initial polarized state to a depolarized state in response to increasing social influence. The nature of this transition depends on the initial disagreement. Initial widely divergent opinions lead to so-called first-order (or explosive) depolarization toward consensus, whereas opinions that are more correlated to begin with lead to second-order consensus. Sequential (or sequential) transition.
Interaction and influence
To test their model, the researchers used data from the American National Election Study on correlated topics such as abortion and religion, and uncorrelated topics such as U.S. immigration and military diplomacy. did. They found that communities consulted on these topics undergo a phase transition from polarization to depolarization in the model’s numerical simulations, and that individuals within the community interact and influence each other. I discovered.
They studied the model under “mean field” conditions, meaning that each individual can interact with every other individual. “Since opinions are described by angles, it was natural to model consensus building as an adjustment of the agent’s orientation,” explains Michele Starnini. “This type of topological coupling was inspired by the Kuramoto model and is practical for small groups. In future work, we plan to test the model in large interactive groups, such as social networks.”
“Another interesting application that we are looking forward to implementing involves measuring an individual’s opinions on multiple topics and their social interactions simultaneously and testing the model in more realistic settings. Masu.”